Quantitative Assessment and Prognostic Value of Myocardial Work Indexes in Septic Cardiomyopathy Patients with Left Ventricular Systolic Dysfunction

Quantitative Assessment and Prognostic Value of Myocardial Work Indexes in Septic Cardiomyopathy Patients with Left Ventricular Systolic Dysfunction | 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 Quantitative Assessment and Prognostic Value of Myocardial Work Indexes in Septic Cardiomyopathy Patients with Left Ventricular Systolic Dysfunction Xu Yanping, Yang Xiaojuan, Wu Jiali, Yang Xue, Pan Lu, Wang Xiaohong, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7179383/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Apr, 2026 Read the published version in Cardiovascular Ultrasound → Version 1 posted 10 You are reading this latest preprint version Abstract Objective : This study was to determine whether myocardial work indexes (MWI) could quantitatively assess left ventricular systolic dysfunction in patients with septic cardiomyopathy (SCM-LVSD) and their predictive efficacy for prognosis in sepsis. Methods : Based on the echocardiographic performance of the left and/or the right ventricular dysfunction, 180 enrolled sepsis were categorized into two groups: the sepsis group and the septic cardiomyopathy (SCM)group . Additionally, the survival group and the mortality group based on their prognosis at 28 days post-admission. Univariate and multivariate logistic regression analyses were performed to explore the relationship between MWI, SCM-LVSD, and prognosis. The diagnostic efficacy of MWI in identifying SCM-LVSD was evaluated using diagnostic tests. Result: ① MWI parameters Comparison: The global work index (GWI), global constructive work (GCW), and global work efficiency (GWE) were significantly reduced in the SCM and mortality groups versus controls (all P <0.01). While, the global wasted work (GWW) was significantly higher in the SCM group than in the sepsis group ( P <0.01). ② Comparison of the diagnostic efficacy in identifying SCM-LVSD: The global longitudinal strain (GLS) demonstrated the highest diagnostic value (area under the receiver operating characteristic curve [AUCs= 0.81], followed by GWI and GCW (AUC=0.77 each)，and GWE (AUC=0.73), the left ventricular ejection fraction (LVEF) and the GWW exhibited lower diagnostic efficacy. ③ Comparison of the prognostic value: GWI, GCW, GLS, and GWE showed the best predictive efficacy for adverse prognosis (AUC of 0.75, 0.74, 0.72, and 0.70, respectively), whereas GWW and LVEF showed limited value. Conclusion : MWI could more accurately quantify the SCM-LVSD. GLS, GWI, and GCW demonstrated higher diagnostic efficacy. Additionally, GWI, GCW, and GWE provided valuable prognostic efficacy for 28-day mortality in sepsis. MWI serves as a valuable tool for the early identification of SCM-LVSD and prognostic assessment of sepsis. Myocardial work indexes Sepsis Septic cardiomyopathy Left ventricular Systolic dysfunction Ejection fraction Global longitudinal strain Figures Figure 1 Figure 2 Figure 3 Introduction Sepsis is a life-threatening organ dysfunction that arises from the body's dysfunctional response to infection [1] . Septic cardiomyopathy (SCM) is an acute cardiac dysfunction syndrome resulting from sepsis [2] . Drosatos et al. [3] confirmed that energy deficiency is the cause of cardiac dysfunction related to sepsis. Patients with SCM frequently experience left ventricular systolic dysfunction (LVSD), which is an independent risk factor for in-hospital mortality among patients with sepsis [4] . Transthoracic echocardiography (TTE) is the most commonly used clinical practice for measuring left ventricular ejection fraction (LVEF) to evaluate left ventricular systolic function. However, LVEF's accuracy diminishes when preload, afterload, or cardiac geometry changes; It can not reflect the intrinsic contraction characteristics of septic myocardium sensitively and accurately [5] . The global longitudinal strain (GLS) of the left ventricle, as determined by speckle tracking echocardiography (STE), is a more sensitive indicator of left ventricular systolic function than LVEF. However, GLS also has the issue of being dependent on afterload [6] . Myocardial work indexes (MWI) were developed using non-invasive brachial artery blood pressure and strain analysis. They have been established as an evaluation method for myocardial energetics and exhibit a strong correlation with oxygen consumption measured by positron emission tomography and local myocardial glucose metabolism [7] . The significance of MWI in the diagnosis and prognosis of SCM-LVSD remains unclear, with limited related studies available. Consequently, we employed MWI to quantitatively assess SCM-LVSD and subsequently investigated the prognostic value of MWI parameters in Sepsis. Materials and Methods 1.1 General information: This study is a prospective cohort study. A total of 180 sepsis patients hospitalized in the ICU of Ningxia Medical University General Hospital between March 2023 and March 2024 were included. Transthoracic echocardiography (TTE) was conducted on the 1st, 3rd, and 5th days post-admission to the ICU. The patients were categorized into two groups based on the presence of left ventricular and/or right ventricular dysfunction: the sepsis group and the septic cardiomyopathy group (SCM group). Additionally, they were divided into survival and death groups according to their survival status 28 days post-discharge. 1.1.1 Inclusion criteria (1) Age 18 to 85 years old; (2) The diagnosis of sepsis met the Sepsis 3.0 diagnostic criteria [8] . 1.1.2 Exclusion criteria (1) Pregnancy status;(2) Post cardiac surgery;(3) Acute coronary syndrome;(4) Moderate or greater aortic and/or mitral regurgitation, mild or greater valve stenosis, and left ventricular outflow tract obstruction;(5) Patients with malignant tumor metastasis;(6) Those with unclear two-dimensional echocardiography images or poor follow-up in more than 2 segments by MWI analysis. 1.1.3 Diagnostic criteria for LVSD: LVEF<50% [9] or absolute GLS 34ml/m 2 , ② The ratio of the mitral orifice early diastolic peak velocity (E-peak) to the mean mitral annulus early diastolic peak velocity (e') E/e ' >14, ③ interventricular septum e<7cm/s or lateral wall e 2.8 m/s, more than two of the four items were positive [6] ; Diagnostic criteria for reduced right ventricular function: tricuspid annular plane systolic excursion (TAPSE) <16mm [6] ; 1.2 Ethics This study adheres to medical ethics standards and has been approved by the Medical Research Ethics Review Committee of Ningxia Medical University General Hospital (No. KYLL-2023-0240). 1.3 Data collection methods 1.3.1(1) General Information and Prognostic Indicators: Data were gathered on patients' gender, age, height, weight, underlying medical conditions, Acute Physiology and Chronic Health Evaluation II (APACHE II) scores, Sequential Organ Failure Assessment (SOFA) scores, infection sites, duration of mechanical ventilation, and 28-day survival or mortality status. (2) Organ function indicators were documented within the first 24 hours of ICU admission: Use of noradrenaline, cumulative fluid balance, serum creatinine concentrations, status of continuous renal replacement therapy, N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels, and serum cardiac troponin I (cTnI) levels. (3) Oxygen therapy parameters and blood gas indicators were recorded within 24 hours of ICU admission: including types of oxygen therapy (invasive ventilation, non-invasive ventilation, and others), duration of mechanical ventilation for patients, and arterial blood lactate levels. 1.3.2 Patients underwent echocardiographic assessments on the 1st, 3rd, and 5th days following admission to the ICU. The GE Vivid E9 ultrasound diagnostic system was employed, featuring an M5S probe with a frequency range of 1.7 to 3.4 MHz, in conjunction with Echo PAC 203 offline analysis software. After completing the transthoracic echocardiography (TTE), the systolic blood pressure (SBP) and diastolic blood pressure (DBP) of the patients' left upper arm were documented. 1.3.2.1 TTE Parameters: The left atrial dimensions are measured in two dimensions, including the anterior-posterior diameter (LAD AP ), up-down diameter (LAD UD ), and left-right diameter (LAD LR ). The left atrial volume (LAV) is calculated using the formula: LAV = (LAD AP ) × (LAD UD ) × (LAD LR ) × 0.523. The left atrial volume index (LAVI) is then determined by dividing the LAV by the body surface area (BSA). The BSA in square meters is calculated with the formula: BSA = 0.0061 × height (cm) + 0.0128 × weight (kg) - 0.1529. Additionally, measure the LV end-diastolic inner diameter (LVDd), LV end-systolic inner diameter (LVDs), The modified biplane simpson method is used to measure the LV end-diastolic volume (EDV), LV end-systolic volume (ESV), stroke volume (SV) and left ventricular ejection fraction (LVEF). Pulsed Doppler (PW) is employed to measure the E and A peaks of mitral valve blood flow spectrum. Tissue Doppler imaging (TDI) assesses the mitral annulus early diastolic peak velocity of the interventricular septum (septal e) and the lateral wall (lateral e), with the average early diastolic peak velocity (e') calculated as (septal e + lateral e) / 2. The E/e' ratio is also determined. Continuous Doppler (CW) measures the peak velocity (V TR ) and peak pressure gradient (PG TR ) of tricuspid regurgitation. The focused right ventricle four-chamber view assesses the tricuspid annular plane systolic excursion (TAPSE) using M-mode, and TDI measures the systolic velocity of tricuspid annulus (s'). The inferior vena cava (IVC) inner diameter and respiratory variation is measured using two-dimensional and M-mode to estimate right atrial pressure. Under fully controlled mechanical ventilation, three respiratory cycles are recorded, measuring the IVC diameter at end-expiration and end-inspiration, with the average values taken. The inferior vena cava distensibility index is calculated as follows: [(end-inspiratory IVC diameter - end-expiratory IVC diameter) / average value] × 100%. An index greater than 15% indicates respiratory variation in the IVC. During spontaneous breathing, three respiratory cycles are similarly recorded, measuring the end-expiratory and end-inspiratory diameters of the IVC, with average values calculated. The end-inspiratory collapse rate of the IVC, known as the collapse index, is calculated as: [(end-expiratory IVC diameter - end-inspiratory IVC diameter) / end-expiratory IVC diameter] × 100%. A collapse index greater than 50% indicates respiratory variation in the IVC. 1.3.2.2 MWI parameters: Collect two-dimensional gray scale images (frame rate 60 - 80 frames/s) of standard apical four-chamber, two-chamber, and three-chamber views for 3 consecutive cardiac cycles and save them. The apical three-chamber cardiac views need to clearly display the mitral valve (MV) and the aortic valve (AV), and the apical four-chamber and two-chamber cardiac views need to completely display LA. Echo PAC software launches Myodardiac Work analysis, measures LV GLS, determines MV and AV open and close times based on PW, and you can enter SBP and DBP and click the Advanced button to obtain MWI parameters, including (1) global work index (GWI),(2) global constructive work (GCW),(3) global wasted work (GWW), and (4) global work efficiency (GWE). 1.3.3 Laboratory related indicators Venous blood samples were taken from enrolled patients within two hours of TTE examination. These samples were sent to the central laboratory of Ningxia Medical University General Hospital for analysis, where cardiac troponin I (cTn-I) and N-terminal pro-B-type natriuretic peptide (NT-proBNP), as well as blood routine, liver, and renal function tests, were measured. 1.4. Repeatability test: An ICU deputy chief physician completed the screening of all sepsis cases and monitoring during image acquisition, a chief echocardiography physician completed the TTE examination and routine data measurement, and MWI parameter measurement and data statistics were completed by two physicians unaware of the study. 1.5 Statistical methods Statistical analysis was conducted using the R programming language (version 4.2.0). Data with a normal distribution are presented as χ ( - ) mean ± standard deviation (S), and comparisons between groups were made using a t-test. For measurement data that did not follow a normal distribution, values are expressed as the median (interquartile range) [M(IQR)], and non-parametric tests were employed for inter-group comparisons. Counting data are presented as the number of cases with percentages (%), and comparisons between groups were performed using either the χ² test or the Fisher exact probability method. Based on the outcomes of single-factor analysis, along with SCM and echocardiography-related guidelines, and expert consensus, multiple logistic regression models were constructed to assess the relationship between MWI and SCM-LVSD. Indicators such as sensitivity, specificity, accuracy, and the optimal cutoff value were calculated through diagnostic experiments, and a receiver operating characteristic (ROC) curve was plotted to evaluate the diagnostic efficacy of MWI for SCM-LVSD and its prognostic value in sepsis patients. A P -value of less than 0.05 indicates that the difference is statistically significant. Results 2.1 Comparison of clinical and TTE data between the sepsis group and the SCM group: Compared with the sepsis group, the SCM group was older and had a higher incidence of supraventricular arrhythmia. The SCM group also exhibited higher APACHE II scores, SOFA scores, NT-pro BNP levels, cTn-I levels, and 28-day mortality rates. Additionally, the SCM group had increased end-systolic volume (ESV), E/e' ratios, and pulmonary artery systolic pressure (PASP), along with decreased stroke volume (SV), left ventricular ejection fraction (LVEF), lateral e, tricuspid annular plane systolic excursion (TAPSE), and s'. These differences were statistically significant ( P < 0.01). In the SCM group, global work index (GWI), global constructive work (GCW), global work efficiency (GWE), and global longitudinal strain (GLS) were significantly reduced, while global wasted work (GWW) and the paced standard deviation (PSD) were significantly increased, all with significant statistical significance ( P < 0.01). Systolic blood pressure (SBP) was lower in the SCM group, the dosage of norepinephrine (NE) was higher, and the peak velocity of tricuspid regurgitation (V TR ) was increased, with these differences being statistically significant compared to the sepsis group ( P < 0.05). There were no statistically significant differences between the groups in terms of gender, the number of combined septic shock cases, heart rate (HR), left ventricular end-diastolic diameter (LVDd), and left atrial volume index (LAVI). (Table 1). Table 1 Comparison of clinical and TTE data between sepsis group and SCM group（n=180， χ ( - ) ±S） sepsis group (n=78) SCM group (n=102) χ²/t p-value Gender (male)a 49(62.82%) 59(57.84%) 0.27 0.602 Age (years)b 53.29±15.11 61.65±14.64 -3.74 <0.01 HR (beats/min)c 97.00(31.75) 98.50(33.50) 3797.50 0.603 Supraventricular arrhythmia [cases (%)]c 3(3.85) 19(18.63) 7.68 <0.01 SBP (mmHg)b 124.78±20.12 117.90±21.65 2.18 0.031 Combined shock [cases (%)]c 39(50.00) 65(63.73) 2.87 0.090 APACHE Ⅱ score c 15.50(6.00) 17.50(8.00) 2985.50 <0.01 SOFA score b 8.08±3.60 9.66±4.00 -2.74 <0.01 NT-pro BNP (pg/ml)c 1045.00(3522.25) 4175.00(10900.00) 2235.50 <0.01 cTn-l(ng/ml)c 0.01(0.07) 0.10(0.60) 2124.50 <0.01 NE dosage (ug/kg.min）c 0.05(0.50) 0.20(0.80) 3179.00 0.016 28-day mortality [cases (%)]c 6(7.69) 39(38.24) 20.39 <0.01 LVDd (mm)b 47.36±4.38 47.14±6.37 0.28 0.783 ESV (ml)c 32.00(13.00) 40.00(34.00) 3078.50 <0.01 SV (ml)c 70.00(19.00) 58.00(21.75) 5550.00 <0.01 LVEF (%)c 68.00(7.00) 62.00(25.00) 5341.50 <0.01 LAVIc 18.12(6.38) 19.21(9.85) 3661.00 0.361 E/e´c 9.00(3.00) 11.00(6.50) 2426.00 <0.01 Lateral e (cm/s)c 11.00(4.00) 8.00(3.50) 6474.00 <0.01 V TR (m/s)c 2.50(0.54) 2.63(0.80) 3112.50 0.012 PASP (mmHg)c 30.00(11.75) 33.00(18.00) 3062.00 <0.01 TAPSE (mm)c 21.00(3.00) 16.00(5.00) 6490.50 <0.01 s´ (cm/s)c 16.00(4.00) 12.00(5.75) 5883.00 <0.01 GWI (mmHg%)b 1643.29±449.23 1115.56±552.73 7.06 <0.01 GCW (mmHg%)c 1867.00(682.50) 1336.50(715.25) 6087.00 <0.01 GWW (mmHg%)c 120.50(106.50) 158.50(136.25) 3077.00 <0.01 GWE (%)c 93.00(7.00) 88.00(11.00) 5802.50 <0.01 GLS (%)c -17.25(3.65) -12.30(5.65) 1500.50 <0.01 PSD (ms)c 48.35(21.83) 64.65(37.75) 2244.00 <0.01 Note: a case (%),b χ ( - ) ±S, cM(IQR), HR is heart rate, SBP is systolic blood pressure, APACHEII score is acute physiology and chronic health status II score, SOFA score is sequential organ failure score, NT-pro BNP is N-terminal pro-B natriuretic peptide, cTn-l is cardiac troponin I, and NE is norepinephrine dose. LVDd is the left ventricular end-diastolic diameter, ESV is the left ventricular end-systolic volume, SV is the left ventricular stroke volume, LVEF is the left ventricular ejection fraction, LAVI is the left atrial volume index, E/e' is the ratio of the mitral orifice early diastolic peak velocity to the mean of the mitral annulus early diastolic peak velocity, Lateral e is the early diastolic peak velocity of the lateral wall mitral annulus, V TR is the tricuspid regurgitation peak velocity, PASP is the pulmonary artery systolic pressure, TAPSE is the tricuspid annulus plane systolic excursion, s´ is the tricuspid annulus systolic velocity, GWI is the global work index, GCW is the global constructive work, GWW is the global wasted work, GWE is the global work efficiency, GLS is the global longitudinal strain of the left ventricular, and PSD is the dispersion of the peak time of the global longitudinal strain of the left ventricular. SCM group is septic cardiomyopathy group. 2.2 Comparison of clinical and TTE data between survival group and death group: Compared to the survival group, the death group exhibited older age, lower systolic blood pressure (SBP), a higher incidence of septic shock and left ventricular systolic dysfunction (LVSD), elevated Acute Physiology and Chronic Health Evaluation II (APACHE II) and Sequential Organ Failure Assessment (SOFA) scores, and increased levels of N-terminal pro-B-type natriuretic peptide (NT-proBNP), cardiac troponin-I (cTn-I), and norepinephrine dosage. Additionally, the death group had a lower stroke volume (SV), lateral e, tricuspid annular plane systolic excursion (TAPSE), and s'. The differences were statistically significant ( P <0.01).Global work index (GWI) global constructive work (GCW),global work efficiency (GWE), and global longitudinal strain (GLS) were significantly decreased, while peak systolic strain dispersion (PSD) was significantly increased in the death group ( P <0.01). Left ventricular end-diastolic diameter (LVDd) was smaller in the death group compared to the survival group, with a statistically significant difference ( P <0.05). However, there was no statistical difference in gender, heart rate (HR), number of supraventricular arrhythmias, end-systolic volume (ESV), left ventricular ejection fraction (LVEF), left atrial volume index (LAVI), E/e´ ratio, the peak velocity of tricuspid regurgitation (V TR ), pulmonary artery systolic pressure (PASP), and global wasted work (GWW) (Table 2). Table 2: Comparison of clinical and TTE data between survival and death group（n=180， χ ( - ) ±S） Survival group(n=135) death group(n=45) χ²/t P value Gender (male)a 83(61.48%) 25(55.56%) 0.28 0.598 Age (years)b 55.90±15.71 64.40±12.45 -3.30 <0.01 HR(beats/min)b 97.82±19.94 107.20±29.18 -2.01 0.050 Supraventricular arrhythmia [case(%)]c 13(9.63) 9(20.00) 2.49 0.115 SBP(mmHg)b 123.69±20.21 112.47±22.17 3.15 <0.01 Combined shock [cases (%)]c 70(51.85) 34(75.56) 6.83 <0.01 APACHEⅡ score c 16.00(7.00） 20.00(10.00） 1832.50 <0.01 SOFA score c 8.00(5.00) 11.00(6.00) -2.74 <0.01 NT-pro BNP(pg/ml)c 1700.00(5927.50) 4210.00(9870.00) 2100.50 <0.01 cTn-l(ng/ml)c 0.03(0.21) 0.07(0.61) 2226.50 <0.01 NE dosage (ug/kg.min）c 0.10(0.50) 0.50(1.40) 1883.00 <0.01 LVDd(mm)b 47.79±5.11 45.56±6.59 2.08 0.042 ESV(ml)c 35.00(21.50) 35.00(32.00) 3199.50 0.593 SV(ml)c 65.00(23.00) 63.00(24.00) 5550.00 <0.01 LVEF(%)c 66.00(12.50) 63.00(24.00) 3443.50 0.180 LAVIc 18.74(8.32) 17.90(7.88) 3435.50 0.189 E/e´c 9.00(4.00) 10.00(5.00) 2828.50 0.489 Lateral e (cm/s)c 10.00(4.50) 8.00(3.00) 3961.00 <0.01 V TR (m/s)c 2.50(0.80) 2.59(0.70) 2869.00 0.578 PASP(mmHg)c 30.00(17.00) 31.00(15.00) 2925.00 0.711 TAPSE(mm)c 19.50(5.00) 15.00(4.00) 4446.50 <0.01 s´(cm/s)c 14.99±4.01 12.22±3.70 4.08 <0.01 Merge LVSD[case (%)]c 63(46.67) 39(86.67) 20.39 <0.01 GWI(mmHg%)b 1467.73±529.53 973.78±541.39 5.39 <0.01 GCW(mmHg%)b 1734.05±548.36 1241.62±579.17 5.14 <0.01 GWW(mmHg%)c 135.00(129.00) 162.00(129.00) 2508.00 0.081 GWE(%)c 91.00(7.50) 85.00(13.00) 4249.50 <0.01 GLS(%)c -15.80(5.80) -12.20(5.00) 1700.50 <0.01 PSD(ms)c 54.80(26.45) 67.20(32.90) 2132.50 <0.01 Note:a case (%),b χ ( - ) ±S,cM(IQR),HR is heart rate, SBP is systolic blood pressure, APACHEII score is acute physiology and chronic health status II score, SOFA score is sequential organ failure score, NT-pro BNP is N-terminal pro-B natriuretic peptide, cTn-l is cardiac troponin I, and NE is norepinephrine dose. LVDd is the left ventricular end-diastolic diameter,ESV is the left ventricular end-systolic volume, SV is the left ventricular stroke volume, LVEF is the left ventricular ejection fraction, LAVI is the left atrial volume index, E/e' is the ratio of the mitral orifice early diastolic peak velocity to the mean of the mitral annulus early diastolic peak velocity, Lateral e is the early diastolic peak velocity of the lateral wall mitral annulus, V TR is the tricuspid regurgitation peak velocity, PASP is the pulmonary artery systolic pressure, TAPSE is the tricuspid annulus plane systolic excursion, s´ is the tricuspid annulus systolic velocity, GWI is the global work index,GCW is the global constructive work,GWW is the global wasted work,GWE is the global work efficiency, GLS is the global longitudinal strain of the left ventricular,PSD is the dispersion of the peak time of the global longitudinal strain of the left ventricular. 2.3 Relationship between MWI and SCM-LVSD The results of the logistic regression model examining the relationship between MWI and SCM-LVSD indicated that, prior to accounting for confounding factors, elevated GWI, GCW, and GWE values were associated with a reduced risk of SCM-LVSD [OR 95% CI: 0.82 (0.76-0.87); 0.84 (0.78-0.89); 0.28 (0.15-0.47)]. After controlling for age, APACHE II score, and NT-pro BNP, the findings remained similar to those without adjustment. Conversely, higher GWW values were linked to an increased risk of SCM-LVSD (OR: 1.29, 95% CI: 0.97-1.74), although this association was not statistically significant (p=0.089). Adjusting for age, APACHE II score, and NT-pro BNP did not alter these results. (Table 3). Table 3 Relationship between MWI and SCM-LVSD (n=180) indicators model 1 model 2 model 3 model 4 OR(95%CI) P value OR(95%CI) P value OR(95%CI) P value OR(95%CI) P value GWI 0.82(0.76-0.87) 0.000 0.80(0.73-0.85) 0.000 0.80(0.74-0.86) 0.000 0.81(0.75-0.88) 0.000 GCW 0.84(0.78-0.89) 0.000 0.81(0.75-0.86) 0.000 0.81(0.75-0.87) 0.000 0.83(0.76-0.89) 0.000 GWW 1.29(0.97-1.74) 0.089 1.16(0.87-1.58) 0.315 1.17(0.87-1.59) 0.315 1.20(0.89-1.64) 0.237 GWE 0.28(0.15-0.47) 0.000 0.29(0.16-0.49) 0.000 0.31(0.17-0.53) 0.000 0.32(0.18-0.56) 0.000 Note: Model 1 is an unadjusted logistic regression model; Model 2 adjusts for age; Model 3 adjusts for APACHE II score based on Model 2, and Model 4 adjusts for NT-pro BNP based on Model 3. 2.4 Relationship between MWI and prognosis of sepsis patients The results of the multivariate logistic regression model for predicting 28-day mortality in patients with sepsis indicated that, before accounting for confounding factors, elevated GWI, GCW, and GWE values were associated with a reduced risk of 28-day mortality in sepsis patients [OR (95% CI): 0.83 (0.77-0.90); 0.84 (0.78-0.91); 0.41 (0.26-0.63)]. After adjusting for age, APACHE II score, and NT-pro BNP levels, the findings remained similar to those without adjustment. Conversely, higher GWW values were linked to an increased risk of 28-day mortality in patients with sepsis (OR: 1.20, 95% CI: 0.89-1.61), although this association was not statistically significant (p=0.218). Adjusting for age, APACHE II score, and NT-pro BNP levels did not alter these results. (Refer to Table 4). Table 4 Relationship between MWI and 28-day death (n=180) indicators model 1 model 2 model 3 model 4 OR(95%CI) p value OR(95%CI) p value OR(95%CI) P value OR(95%CI) P value GWI 0.83(0.77-0.90) 0.000 0.81(0.74-0.88) 0.000 0.84(0.76-0.91) 0.000 0.83(0.76-0.91) 0.000 GCW 0.84(0.78-0.91) 0.000 0.82(0.75-0.89) 0.000 0.85(0.77-0.92) 0.000 0.84(0.77-0.91) 0.000 GWW 1.20(0.89-1.61) 0.218 1.10(0.80-1.49) 0.553 1.10(0.77-1.55) 0.577 1.11(0.77-1.56) 0.560 GWE 0.41(0.26-0.63) 0.000 0.42(0.26-0.64) 0.000 0.45(0.27-0.72) 0.001 0.45(0.27-0.73) 0.001 Note: Model 1 is an unadjusted logistic regression model; Model 2 adjusts for age; Model 3 adjusts for APACHE II score based on Model 2, and Model 4 adjusts for NT-pro BNP based on Model 3. 2.5 Diagnostic efficacy of MWI in SCM-LVSD Diagnostic test results indicated that GWI, GCW, GWW, GWE, LVEF, GLS, cTn-I, and NT-proBNP all possess certain diagnostic value for SCM-LVSD. Among these, GLS exhibits the highest diagnostic efficiency, with an AUC of 0.81, followed by GWI (AUC of 0.77) and GCW (AUC of 0.77), then GWE (AUC of 0.73), and cTn-I (AUC of 0.72). The diagnostic efficiency of LVEF and GWW is relatively poor, with AUCs of 0.67 and 0.61, respectively. (Table 5). Table 5 ROC curve results of MWI indicators in diagnosing SCM-LVSD（n=180， χ ( - ) ±S） project AUC （95%CI） cutoff value sensitivity specificity accuracy youden index standard error p-value GWI(mmHg%) 0.77(0.71-0.84) 1167.50 62.75% 89.74% 74.17% 1.52 0.03 0.000 GCW(mmHg%) 0.77(0.70-0.83) 1640.50 74.51% 73.08% 73.89% 1.49 0.04 0.000 GWW(mmHg%) 0.61(0.53-0.70) 130.50 69.61% 60.26% 63.33% 1.24 0.04 0.008 GWE(%) 0.73(0.66-0.80) 92.50 78.92% 60.26% 69.44% 1.38 0.04 0.000 LVEF(%) 0.67(0.59-0.75) 59.5 43.63% 94.23% 63.89% 1.35 0.04 0.000 GLS(%) 0.81(0.75-0.87) -14.95 71.57% 80.77% 75.00% 1.51 0.03 0.000 cTn-I(ng/ml) 0.73(0.66-0.80) 0.03 80.39% 64.10% 72.50% 1.44 0.04 0.000 NT-proBNP(pg/ml) 0.72(0.64-0.79) 2107.50 72.06% 71.15% 70.56% 1.41 0.04 0.000 Note: AUC: area under the curve; 95% CI: 95% confidence interval. 2.6 Effectiveness of MWI in evaluating the prognosis of patients with sepsis The diagnostic test results indicated that GWI, GCW, GWW, GWE, LVEF, GLS, cTn-I, and NT-proBNP all possess some prognostic value for predicting 28-day mortality in sepsis patients. GWI exhibited the highest prognostic value with an Area Under the Curve (AUC) of 0.75, followed by GCW (AUC of 0.74), GLS (AUC of 0.72), and GWE (AUC of 0.70). NT-pro BNP (AUC of 0.65) and cTn-I (AUC of 0.63) were also significant, albeit less so. In contrast, GWW and LVEF demonstrated poor prognostic evaluation, with AUCs of 0.59 and 0.57, respectively. (Refer to Table 6). Table 6 Evaluation of MWI on the prognosis of patients with sepsis（n=180， χ ( - ) ±S） project AUC（95%CI） cutoff value sensitivity specificity accuracy youden index standard error p-value GWI (mmHg%) 0.75(0.66-0.83) 1248.50 77.78% 68.52% 71.11% 1.44 0.04 0.000 GCW (mmHg%) 0.74(0.66-0.83) 1600.50 84.44% 60.00% 66.11% 1.44 0.04 0.000 GWW (mmHg%) 0.59(0.49-0.68) 130.50 73.33% 51.85% 58.06% 1.24 0.04 0.07 GWE (%) 0.70(0.61-0.79) 85.50 62.22% 76.30% 71.67% 1.37 0.04 0.000 LVEF (%) 0.57(0.46-0.67) 60.25% 50.00% 75.56% 69.72% 1.22 0.05 0.21 GLS (%) 0.72(0.64-0.80) -14.55 77.78% 63.70% 67.78% 1.41 0.04 0.000 cTn-I (ng/ml) 0.63(0.54-0.73) 0.05 66.67% 67.04% 68.61% 1.26 0.04 0.006 NT-pro BNP (pg/ml) 0.65(0.57-0.74) 1115.00 88.89% 44.81% 56.11% 1.33 0.04 0.000 Note: AUC: area under the curve; 95% CI: 95% confidence interval. Discussion Sepsis is a prevalent acute and critical illness in medicine and surgery, characterized by high morbidity and mortality rates. The heart is particularly susceptible to sepsis, and the focus of Trans-thoracic echocardiography (TTE) observations is on identifying abnormal cardiac function [12] . Sepsis cardiomyopathy (SCM) is acute heart failure caused by sepsis. Of the 180 sepsis patients enrolled, 102 exhibited various types of cardiac dysfunction, with a 56.7% incidence of SCM. The left ventricular ejection fraction (LVEF) in the SCM group was 62.00%. It is possible that left ventricular myocardial inhibition was masked by reduced afterload, resulting in a normal LVEF. The diagnostic utility of LVEF for SCM-induced left ventricular systolic dysfunction (LVSD) was found to be low (AUC: 0.67). Previous studies that used an LVEF<50% to diagnose SCM [13, 14] led to numerous missed diagnoses. The 28-day mortality rate in this study was 7.7% for the sepsis group and 38.2% for the SCM group. The presence of SCM significantly increased the mortality rate among sepsis patients [15] . Early identification of SCM and timely intervention are crucial in reducing sepsis-related deaths. Global longitudinal strain (GLS) can detect more subtle LVSD when LVEF appears normal and is currently the preferred method for studying the relationship between left ventricular systolic function and prognosis in SCM patients [16] . In the two grouping methods used in this study, the GLS of the SCM group was significantly lower than that of the sepsis group, and the death group's GLS was lower compared to the survival group, at -12.30%(5.65%) and -12.20%(5.00%) respectively. Patients with sepsis or septic shock who receive systemic vasopressors and rapid fluid resuscitation often experience significant fluctuations in blood pressure. In this study, systolic blood pressure (SBP) differed between the sepsis group and the SCM group, as well as between the survival group and the death group. An increase in afterload leads to a decrease in global longitudinal strain (GLS) values, which can result in clinicians misjudging the true left ventricular (LV) systolic function [17] . The myocardial work index (MWI) is a novel method for non-invasively constructing a LV pressure-strain loop (PSL) to quantitatively assess myocardial systolic function. It allows the study of LV systolic function under varying afterload conditions and correlates well with biochemical indicators such as NT-pro BNP for diagnosing cardiac dysfunction [18] . The parameters of MWI include global work index (GWI), global constructive work (GCW), global wasted work (GWW), and global work efficiency (GWE). GWI represents the area of the PSL, which corresponds to LV systolic work per stroke; GCW is the work done that facilitates ejection, GWW equals GCW minus GWI, representing the work that does not contribute to ejection; and GWE equals GCW divided by the sum of GCW and GWW, multiplied by 100%, reflecting the efficiency of myocardial work. Both GWI and GCW are considered indicators of the overall efficiency of the LV, and decreases in their values suggest LV systolic dysfunction (LVSD). GWI is closely related to myocardial oxygen consumption, while GCW is secondary [19] . The sepsis group in this study (average age 53.29±15.11 years) and the MWI data from a study by Ding Xueyan et al. [20] on 64 healthy adult volunteers (average age 52.1±10.7 years) were significantly lower. The analysis suggested that the heart is a high-energy-consuming organ, and under sepsis, the LV faces a conflict between energy supply and demand due to inflammatory storms, metabolic disorders, mitochondrial damage, and pressure stress after norepinephrine (NE) application. Additionally, the early inflammatory response in sepsis leads to decreased sensitivity of cardiomyocytes to Ca2+, mitochondrial dysfunction, and down-regulation of β-adrenergic receptor expression, resulting in myocardial inhibition [21] . Compared with the sepsis group, the SCM group showed significantly reduced GWI, GCW, and GWE, and a significantly increased GWW, indicating more increased myocardial energy loss and significant LVSD. The analysis reasons were: (1) SCM patients were older (61.65±14.64 years) than sepsis patients, and increased wall rigidity in elderly patients affects LV filling, while heart rate (HR) is accelerated by systemic inflammatory response syndrome and shortened LV filling time, potentially causing a reduction in stroke volume (SV), GWI, and GCW; (2) The SCM group had an increased pulmonary artery systolic pressure (PASP) of 33mmHg, related to lung injury and hypoxemia caused by infection. A slight increase in PASP can lead to a significant decrease in right ventricular stroke volume, triggering interventricular interactions and causing mechanical asynchrony during the normal cardiac cycle [22] . The SCM group also had a prolonged PSD that is a strain parameter used to evaluate LV systolic synchrony. Mechanical asynchrony results in wasted work on the asynchronous diastolic segments [20] . A significant increase in GWW will further deteriorate LV pump function [22] ; (3) The use of high-dose NE may increase afterload after correcting severe distributive shock and myocardial inhibition becomes apparent. Therefore, MWI can detect subclinical LVSD and assist in assessing myocardial efficiency in SCM patients. Hedwig et al. [18] proposed that a GWI<500mmHg% is a predictor of significant left ventricular (LV) remodeling, severe impairment of left ventricular ejection fraction (LVEF), and a significant increase in N-terminal pro-B-type natriuretic peptide (NT-pro BNP). Chan et al. [19] found that significant reductions in GWI and GWE suggested that LV myocardial systolic function in patients with dilated cardiomyopathy was significantly impaired. The results of the Logistic regression model in this study showed that the higher the GWI, GCW, and GWE values, the lower the risk of developing septic cardiomyopathy with left ventricular systolic dysfunction (SCM-LVSD), and the higher the GWW value, the higher the risk of developing SCM-LVSD; global longitudinal strain (GLS) has the highest diagnostic power for SCM-LVSD, with an area under the curve (AUC) of 0.81, followed by GWI (AUC of 0.77) and GCW (AUC of 0.77), and then by GWE (AUC of 0.73), cardiac troponin I (cTn-I) (AUC of 0.73), and NT-pro BNP (AUC of 0.72). The diagnostic power of LVEF and GWW is poor. The presence of LVSD had significant predictive value for 28-day mortality in sepsis patients. Logistic regression model results showed that the higher the GWI, GCW, and GWE values, the lower the risk of 28-day mortality in sepsis patients. The highest prognostic value for 28-day mortality in sepsis patients was GWI with an AUC of 0.75, followed by GCW (AUC of 0.74), GLS (AUC of 0.72), and GWE (AUC of 0.70), and then by NT-pro BNP (AUC of 0.65) and cTn-I (AUC of 0.63); the prognostic evaluation effect of GWW and LVEF is poor. SCM refers to a form of heart failure caused by energy deficit in the heart due to sepsis, essentially characterized by reduced cardiac work efficiency. As a novel technique for evaluating left ventricular (LV) myocardial contraction efficiency, Myocardial Work Index (MWI) enables clinicians to better understand LV systolic performance under different afterload conditions [23]. It accurately reflects myocardial oxygen consumption and can be regarded as a comprehensive and powerful tool for assessing LV systolic function and predicting prognosis in sepsis patients. This study has several limitations: First, as a single-center prospective cohort study, the relatively small sample size may diminish statistical power and impact the generalizability of the study's conclusions; second, the current diagnosis of septic cardiomyopathy (SCM) lacks internationally recognized diagnostic criteria, which may result in selection bias and classification heterogeneity. At the methodological level, although core ultrasound indicators such as left and right ventricular function were systematically evaluated, a multiple organ dysfunction assessment system was not integrated, which may affect the comprehensive judgment of clinical phenotypes. Additionally, some patients had received positive inotropic medication intervention before echocardiography examination, and while stratified analysis was used, there may still be residual confounding factors that were not fully controlled. Therefore, further prospective large-sample, multi-center studies are still needed to clarify the evaluative and prognostic roles of MWI in SCM-LVSD. Declarations Conflict of interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Author Contribution Xu Yanping : collect data and write paperYang Xiaojuan :subject design and application for fundWu Jiali:methodology and statisticsYang Xue ,Pan Lu,Yang Ying, Wang Ying and Cao Wei:project implementation and measurementWang Xiaohong and Na Lisha:supervision References EvansA L. RhodesW. AlhazzaniM. M. LevyM. AntonelliR. FerrerA. KumarJ. E. SevranskyC. L. SprungM. E. Nunnally.Surviving Sepsis Campaign: International Guidelines for Management of Sepsis and Septic ShockCrit. Care Med. 2021. 10.1097/ccm.0000000000005337 . Sanfilippo F, Orde S, Oliveri F, et al. The challenging diagnosis of septic cardiomyopathy. 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PalaidimosSepsis-induced cardiomyopathy is associated with higher mortality rates in patients with sepsis. Acute Crit Care. 2021. 10.4266/acc.2021.00234 . Ehrman RR, Moore SC, Favot MJ, Akers KG, Gallien JZ, Welch RD, Abidov A, Sherwin RL, Levy PD. Scientific Letter to the Editor: Need for a Definitive Study of Global Longitudinal Strain for Prognostication in Septic Cardiomyopathy. Elsevier BV. 2019;32(4):549–e5523. https://doi.org/10.1016/j.echo.2018.12.005 . Roemer S, Jaglan A, Santos D, et al. The utility of myocardial work in clinical practice[J]. J Am Soc Echocardiogr. 2021;34(8):807–18. 10.1016/j.echo.2021.04.013 . Hedwig F, Soltani S, Stein J, et al. Global work index correlates with established prognostic parameters ofheart failure[J]. Echocardiography. 2020;37(3):412–20. 10.1111/echo.14612 . Chan J, Edwards N, Khandheria BK, et al. A new approach to assess myocardial work by non-invasive left ventricular pressure-strain relations in hypertension and dilated cardiomyopathy [J]. Eur Heart J Cardiovasc Imaging. 2018;20(1):31–9. 10.1093/ehjci/jey131 . Ding Xueyan L, Yidan C, Qizhe, et al. Evaluation of Left Ventricular Pressure-Strain Loops in Assessing Myocardial Work in Healthy Adults Using Echocardiography. Chin J Ultrasound Med. 2021;37(6):655–8. Liu, Yina, Ma Xiaochun. Selection of Vasopressor Agents in Septic Cardiomyopathy [J/OL]. Chin J Electron Crit Care Med. 2020;6(2):128–31. Cheng Xiansheng. Interdependence of Ventricles and Mechanical Function Patterns of Right Heart Myocardium. [J]. Chin J Cardiovasc Dis. 2020;48(10):814–22. Fan Jingdong L, Min S. Advances in the Application of Ultrasound Myocardial Work Technique in Evaluating Left Ventricular Dysfunction Due to Different Etiologies. [J]. J Clin Ultrasound Med. 2023;25(2):137–41. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 06 Apr, 2026 Read the published version in Cardiovascular Ultrasound → Version 1 posted Editorial decision: Revision requested 26 Oct, 2025 Reviews received at journal 22 Oct, 2025 Reviewers agreed at journal 29 Sep, 2025 Reviews received at journal 27 Sep, 2025 Reviewers agreed at journal 23 Sep, 2025 Reviewers agreed at journal 20 Aug, 2025 Reviewers invited by journal 07 Aug, 2025 Editor assigned by journal 21 Jul, 2025 Submission checks completed at journal 21 Jul, 2025 First submitted to journal 21 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7179383","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":497308675,"identity":"0244bda5-e4fe-47bd-a267-143d05115063","order_by":0,"name":"Xu 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16:11:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7179383/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7179383/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12947-026-00370-w","type":"published","date":"2026-04-06T15:57:21+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":89066255,"identity":"a6fe8cac-9566-44ab-a614-e07fa99c6736","added_by":"auto","created_at":"2025-08-14 10:42:37","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":97402,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison of myocardial work maps in patients with Sepsis and SCM\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7179383/v1/0fb84b9c15c801633cc13738.jpg"},{"id":89066713,"identity":"6531e820-37c4-4c63-8928-081c1cdfa671","added_by":"auto","created_at":"2025-08-14 10:42:48","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":105729,"visible":true,"origin":"","legend":"\u003cp\u003eThe maximum area under the curve of receiver operating characteristic (ROC) curves for diagnosis of SCM-LVSD by each indicator is 0.77, GCW is 0.77, GWW is 0.61, GWE is 0.73, LVEF is 0.67, GLS is 0.81, cTn-I is 0.73, NT-pro BNP is 0.72\u003c/p\u003e\n\u003cp\u003eNote: GWI is global work index,GCW is global constructive work,GWE is global work efficiency, GWW is global wasted work,GLS is global longitudinal strain of the left ventricular,LVEF is left ventricular ejection fraction ,cTn-I is cardiac troponin I, NT-pro BNP is N-terminal pro-B type natriuretic peptide.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7179383/v1/4f4bea24cd00073b4d091ba8.jpg"},{"id":89066326,"identity":"51e4ebdf-b44a-4f75-8fe6-4b6b945ebf29","added_by":"auto","created_at":"2025-08-14 10:42:38","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":114955,"visible":true,"origin":"","legend":"\u003cp\u003eThe maximum area under the curve of receiver operating characteristic (ROC) curves for evaluating the prognosis of patients with sepsis by each indicator is 0.75, 0.74, 0.70, 0.59, 0.72, 0.57, 0.63, and 0.65\u003c/p\u003e\n\u003cp\u003eNote: GWI is global work index, GCW is global effective work, GWE is global work efficiency, GWW is global ineffective work, GLS is global longitudinal strain of the left ventricle, EF is left ventricular ejection fraction, cTn-l is cardiac troponin I, NT-pro BNP is N-terminal pro-B type natriuretic peptide\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7179383/v1/177241c214b8e916170a4c36.jpg"},{"id":106810675,"identity":"a70f87b4-6b65-4de6-9a48-db49e582b488","added_by":"auto","created_at":"2026-04-13 16:16:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1127152,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7179383/v1/bc948b1c-ff47-4625-8199-0cd692202caa.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Quantitative Assessment and Prognostic Value of Myocardial Work Indexes in Septic Cardiomyopathy Patients with Left Ventricular Systolic Dysfunction","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSepsis is a life-threatening organ dysfunction that arises from the body's dysfunctional response to infection \u003csup\u003e[1]\u003c/sup\u003e. Septic cardiomyopathy (SCM) is an acute cardiac dysfunction syndrome resulting from sepsis \u003csup\u003e[2]\u003c/sup\u003e. Drosatos et al. \u003csup\u003e[3]\u003c/sup\u003e confirmed that energy deficiency is the cause of cardiac dysfunction related to sepsis. Patients with SCM frequently experience left ventricular systolic dysfunction (LVSD), which is an independent risk factor for in-hospital mortality among patients with sepsis \u003csup\u003e[4]\u003c/sup\u003e. Transthoracic echocardiography (TTE) is the most commonly used clinical practice for measuring left ventricular ejection fraction (LVEF) to evaluate left ventricular systolic function. However, LVEF's accuracy diminishes when preload, afterload, or cardiac geometry changes; It can not reflect the intrinsic contraction characteristics of septic myocardium sensitively and accurately\u003csup\u003e[5]\u003c/sup\u003e. The global longitudinal strain (GLS) of the left ventricle, as determined by speckle tracking echocardiography (STE), is a more sensitive indicator of left ventricular systolic function than LVEF. However, GLS also has the issue of being dependent on afterload \u003csup\u003e[6]\u003c/sup\u003e. Myocardial work indexes (MWI) were developed using non-invasive brachial artery blood pressure and strain analysis. They have been established as an evaluation method for myocardial energetics and exhibit a strong correlation with oxygen consumption measured by positron emission tomography and local myocardial glucose metabolism \u003csup\u003e[7]\u003c/sup\u003e. The significance of MWI in the diagnosis and prognosis of SCM-LVSD remains unclear, with limited related studies available. Consequently, we employed MWI to quantitatively assess SCM-LVSD and subsequently investigated the prognostic value of MWI parameters in Sepsis.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e1.1 General information:\u0026nbsp;This study is a prospective cohort study. A total of 180\u0026nbsp;sepsis\u0026nbsp;patients hospitalized in the ICU of Ningxia Medical University General Hospital between March 2023 and March 2024 were included. Transthoracic echocardiography (TTE) was conducted on the 1st, 3rd, and 5th days post-admission to the ICU. The patients were categorized into two groups based on the presence of left ventricular and/or right ventricular dysfunction: the sepsis group and the septic cardiomyopathy group (SCM group). Additionally, they were divided into survival and death groups according to their survival status 28 days post-discharge.\u003c/p\u003e\n\u003cp\u003e1.1.1 Inclusion criteria (1) Age 18 to 85 years old; (2) The diagnosis of\u0026nbsp;sepsis\u0026nbsp;met the Sepsis 3.0 diagnostic criteria \u003csup\u003e[8]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e1.1.2 Exclusion criteria (1) Pregnancy status;(2) Post cardiac surgery;(3) Acute coronary syndrome;(4) Moderate or greater aortic and/or mitral regurgitation, mild or greater valve stenosis, and left ventricular outflow tract obstruction;(5) Patients with malignant tumor metastasis;(6) Those with unclear two-dimensional echocardiography images or poor follow-up in more than 2 segments by MWI analysis.\u003c/p\u003e\n\u003cp\u003e1.1.3 Diagnostic criteria for LVSD: LVEF\u0026lt;50% \u003csup\u003e[9]\u003c/sup\u003e or absolute GLS \u0026lt;17% \u003csup\u003e[10, 11]\u003c/sup\u003e;\u003c/p\u003e\n\u003cp\u003eDiagnostic criteria for reduced left ventricular diastolic function: ① left atrial volume index (LAVI) \u0026gt;34ml/m\u003csup\u003e2\u003c/sup\u003e, ② The ratio of the mitral orifice early diastolic peak velocity (E-peak) to the mean mitral annulus early diastolic peak velocity (e') E/e ' \u0026gt;14, ③ interventricular septum e\u0026lt;7cm/s or lateral wall e \u0026lt;10cm/s, ④tricuspid regurgitation peak velocity (V\u003csub\u003eTR\u003c/sub\u003e) \u0026gt; 2.8 m/s, more than two of the four items were positive \u003csup\u003e[6]\u003c/sup\u003e;\u003c/p\u003e\n\u003cp\u003eDiagnostic criteria for reduced right ventricular function: tricuspid annular plane systolic excursion (TAPSE) \u0026lt;16mm \u003csup\u003e[6]\u003c/sup\u003e;\u003c/p\u003e\n\u003cp\u003e1.2 Ethics\u003c/p\u003e\n\u003cp\u003eThis study adheres to medical ethics standards and has been approved by the Medical Research Ethics Review Committee of Ningxia Medical University General Hospital (No. KYLL-2023-0240).\u003c/p\u003e\n\u003cp\u003e1.3 Data collection methods\u003c/p\u003e\n\u003cp\u003e1.3.1(1)\u0026nbsp;General Information and Prognostic Indicators: Data were gathered on patients' gender, age, height, weight, underlying medical conditions, Acute Physiology and Chronic Health Evaluation II (APACHE II) scores, Sequential Organ Failure Assessment (SOFA) scores, infection sites, duration of mechanical ventilation, and 28-day survival or mortality status. (2) Organ function indicators were documented within the first 24 hours of ICU admission: Use of noradrenaline, cumulative fluid balance, serum creatinine concentrations, status of continuous renal replacement therapy, N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels, and serum cardiac troponin I (cTnI) levels. (3) Oxygen therapy parameters and blood gas indicators were recorded within 24 hours of ICU admission: including types of oxygen therapy (invasive ventilation, non-invasive ventilation, and others), duration of mechanical ventilation for patients, and arterial blood lactate levels.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1.3.2\u0026nbsp;Patients underwent echocardiographic assessments on the 1st, 3rd, and 5th days following admission to the ICU. The GE Vivid E9 ultrasound diagnostic system was employed, featuring an M5S probe with a frequency range of 1.7 to 3.4 MHz, in conjunction with Echo PAC 203 offline analysis software. After completing the transthoracic\u0026nbsp;echocardiography\u0026nbsp;(TTE), the systolic blood pressure (SBP) and diastolic blood pressure (DBP) of the patients' left upper arm were documented.\u003c/p\u003e\n\u003cp\u003e1.3.2.1 TTE Parameters: The left atrial dimensions are measured in two dimensions, including the anterior-posterior diameter (LAD\u003csub\u003eAP\u003c/sub\u003e), up-down diameter (LAD\u003csub\u003eUD\u003c/sub\u003e), and left-right diameter (LAD\u003csub\u003eLR\u003c/sub\u003e). The left atrial volume (LAV) is calculated using the formula: LAV = (LAD\u003csub\u003eAP\u003c/sub\u003e)\u0026nbsp;×\u0026nbsp;(LAD\u003csub\u003eUD\u003c/sub\u003e)\u0026nbsp;×\u0026nbsp;(LAD\u003csub\u003eLR\u003c/sub\u003e)\u0026nbsp;×\u0026nbsp;0.523. The left atrial volume index (LAVI) is then determined by dividing the LAV by the body surface area (BSA). The BSA in square meters is calculated with the formula: BSA = 0.0061\u0026nbsp;×\u0026nbsp;height (cm) + 0.0128\u0026nbsp;×\u0026nbsp;weight (kg) - 0.1529. Additionally, measure the LV end-diastolic inner diameter (LVDd), LV end-systolic inner diameter (LVDs), The modified biplane simpson method is used to measure the LV end-diastolic volume (EDV), LV end-systolic volume (ESV), stroke volume (SV) and left ventricular ejection fraction (LVEF). Pulsed Doppler (PW) is employed to measure the E and A peaks of mitral valve blood flow spectrum. Tissue Doppler imaging (TDI) assesses the mitral annulus early diastolic peak velocity of the interventricular septum (septal e) and the lateral wall (lateral e), with the average early diastolic peak velocity (e') calculated as (septal e\u003csub\u003e\u0026nbsp;+\u003c/sub\u003e lateral e) / 2. The E/e' ratio is also determined. Continuous Doppler (CW) measures the peak velocity (V\u003csub\u003eTR\u003c/sub\u003e) and peak pressure gradient (PG\u003csub\u003eTR\u003c/sub\u003e) of tricuspid regurgitation. The focused right ventricle four-chamber view assesses the tricuspid annular plane systolic excursion (TAPSE) using M-mode, and TDI measures the systolic velocity of tricuspid annulus (s'). The inferior vena cava (IVC) inner diameter and respiratory variation is measured using two-dimensional and M-mode to estimate right atrial pressure. Under fully controlled mechanical ventilation, three respiratory cycles are recorded, measuring the IVC diameter at end-expiration and end-inspiration, with the average values taken. The inferior vena cava distensibility index is calculated as follows: [(end-inspiratory IVC diameter - end-expiratory IVC diameter) / average value] × 100%. An index greater than 15% indicates respiratory variation in the IVC. During spontaneous breathing, three respiratory cycles are similarly recorded, measuring the end-expiratory and end-inspiratory diameters of the IVC, with average values calculated. The end-inspiratory collapse rate of the IVC, known as the collapse index, is calculated as: [(end-expiratory IVC diameter - end-inspiratory IVC diameter) / end-expiratory IVC diameter] × 100%. A collapse index greater than 50% indicates respiratory variation in the IVC.\u003c/p\u003e\n\u003cp\u003e1.3.2.2 MWI parameters: Collect two-dimensional gray scale images (frame rate 60 - 80 frames/s) of standard apical four-chamber, two-chamber, and three-chamber views for 3 consecutive cardiac cycles and save them. The apical three-chamber cardiac views need to clearly display the mitral valve (MV) and the aortic valve (AV), and the apical four-chamber and two-chamber cardiac views need to completely display LA. Echo PAC software launches Myodardiac Work analysis, measures LV GLS, determines MV and AV open and close times based on PW, and you can enter SBP and DBP and click the Advanced button to obtain MWI parameters, including (1) global work index (GWI),(2) global constructive work (GCW),(3) global wasted work (GWW), and (4) global work efficiency (GWE).\u003c/p\u003e\n\u003cp\u003e1.3.3 Laboratory related indicators\u003c/p\u003e\n\u003cp\u003eVenous blood samples were taken from enrolled patients within two hours of TTE examination. These samples were sent to the central laboratory of Ningxia Medical University General Hospital for analysis, where cardiac troponin I (cTn-I) and N-terminal pro-B-type natriuretic peptide (NT-proBNP), as well as blood routine, liver, and renal function tests, were measured.\u003c/p\u003e\n\u003cp\u003e1.4. Repeatability test: An ICU deputy chief physician completed the screening of all sepsis cases and monitoring during image acquisition, a chief echocardiography physician completed the TTE examination and routine data measurement, and MWI parameter measurement and data statistics were completed by two physicians unaware of the study.\u003c/p\u003e\n\u003cp\u003e1.5 Statistical methods\u003c/p\u003e\n\u003cp\u003eStatistical analysis was conducted using the R programming language (version 4.2.0). Data with a normal distribution are presented as \u003cruby\u003eχ\u003crp\u003e(\u003c/rp\u003e\n \u003crt\u003e-\u003c/rt\u003e\n \u003crp\u003e)\u003c/rp\u003e\n \u003c/ruby\u003emean ± standard deviation (S), and comparisons between groups were made using a t-test. For measurement data that did not follow a normal distribution, values are expressed as the median (interquartile range) [M(IQR)], and non-parametric tests were employed for inter-group comparisons. Counting data are presented as the number of cases with percentages (%), and comparisons between groups were performed using either the χ² test or the Fisher exact probability method. Based on the outcomes of single-factor analysis, along with SCM and echocardiography-related guidelines, and expert consensus, multiple logistic regression models were constructed to assess the relationship between MWI and SCM-LVSD. Indicators such as sensitivity, specificity, accuracy, and the optimal cutoff value were calculated through diagnostic experiments, and a receiver operating characteristic (ROC) curve was plotted to evaluate the diagnostic efficacy of MWI for SCM-LVSD and its prognostic value in sepsis patients. A \u003cem\u003eP\u003c/em\u003e-value of less than 0.05 indicates that the difference is statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e2.1 Comparison of clinical and TTE data between the sepsis group and the SCM group:\u003c/p\u003e\n\u003cp\u003eCompared with the sepsis group, the SCM group was older and had a higher incidence of supraventricular arrhythmia. The SCM group also exhibited higher APACHE II scores, SOFA scores, NT-pro BNP levels, cTn-I levels, and 28-day mortality rates. Additionally, the SCM group had increased end-systolic volume (ESV), E/e\u0026apos; ratios, and pulmonary artery systolic pressure (PASP), along with decreased stroke volume (SV), left ventricular ejection fraction (LVEF), lateral e, tricuspid annular plane systolic excursion (TAPSE), and s\u0026apos;. These differences were statistically significant (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01). In the SCM group, global work index (GWI), global constructive work (GCW), global work efficiency (GWE), and global longitudinal strain (GLS) were significantly reduced, while global wasted work (GWW) and the paced standard deviation (PSD) were significantly increased, all with significant statistical significance (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.01). Systolic blood pressure (SBP) was lower in the SCM group, the dosage of norepinephrine (NE) was higher, and the peak velocity of tricuspid regurgitation (V\u003csub\u003eTR\u003c/sub\u003e) was increased, with these differences being statistically significant compared to the sepsis group (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05). There were no statistically significant differences between the groups in terms of gender, the number of combined septic shock cases, heart rate (HR), left ventricular end-diastolic diameter (LVDd), and left atrial volume index (LAVI). (Table 1).\u003c/p\u003e\n\u003cp\u003eTable 1 Comparison of clinical and TTE data between sepsis group and SCM group（n=180，\u003cruby\u003e\u0026chi;\u003crp\u003e(\u003c/rp\u003e\n \u003crt\u003e-\u003c/rt\u003e\n \u003crp\u003e)\u003c/rp\u003e\u0026nbsp;\n \u003c/ruby\u003e\u0026plusmn;S）\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003esepsis group (n=78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eSCM group (n=102)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026chi;\u0026sup2;/t\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eGender (male)a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e49(62.82%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003e59(57.84%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e0.602\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eAge (years)b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e53.29\u0026plusmn;15.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e61.65\u0026plusmn;14.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e-3.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eHR (beats/min)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e97.00(31.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e98.50(33.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e3797.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e0.603\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eSupraventricular arrhythmia [cases (%)]c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e3(3.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e19(18.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e7.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eSBP (mmHg)b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e124.78\u0026plusmn;20.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e117.90\u0026plusmn;21.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e2.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eCombined shock [cases (%)]c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e39(50.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e65(63.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e2.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e0.090\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eAPACHE Ⅱ score c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e15.50(6.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e17.50(8.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e2985.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eSOFA score b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e8.08\u0026plusmn;3.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e9.66\u0026plusmn;4.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e-2.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eNT-pro BNP (pg/ml)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e1045.00(3522.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e4175.00(10900.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e2235.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003ecTn-l(ng/ml)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e0.01(0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.10(0.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e2124.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eNE dosage (ug/kg.min）c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e0.05(0.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.20(0.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e3179.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e28-day mortality [cases\u0026nbsp;(%)]c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e6(7.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e39(38.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e20.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eLVDd (mm)b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e47.36\u0026plusmn;4.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e47.14\u0026plusmn;6.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e0.783\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eESV (ml)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e32.00(13.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e40.00(34.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e3078.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eSV (ml)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e70.00(19.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e58.00(21.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e5550.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eLVEF (%)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e68.00(7.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e62.00(25.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e5341.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eLAVIc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e18.12(6.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e19.21(9.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e3661.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e0.361\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eE/e\u0026acute;c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e9.00(3.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e11.00(6.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e2426.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eLateral e (cm/s)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e11.00(4.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e8.00(3.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e6474.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eV\u003csub\u003eTR\u0026nbsp;\u003c/sub\u003e(m/s)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e2.50(0.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e2.63(0.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e3112.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003ePASP (mmHg)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e30.00(11.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e33.00(18.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e3062.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eTAPSE (mm)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e21.00(3.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e16.00(5.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e6490.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003es\u0026acute; (cm/s)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e16.00(4.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e12.00(5.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e5883.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eGWI (mmHg%)b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e1643.29\u0026plusmn;449.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e1115.56\u0026plusmn;552.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e7.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eGCW (mmHg%)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e1867.00(682.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e1336.50(715.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e6087.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eGWW (mmHg%)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e120.50(106.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e158.50(136.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e3077.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eGWE (%)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e93.00(7.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e88.00(11.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e5802.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eGLS (%)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e-17.25(3.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e-12.30(5.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e1500.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003ePSD (ms)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e48.35(21.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e64.65(37.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e2244.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: a case (%),b\u003cruby\u003e\u0026chi;\u003crp\u003e(\u003c/rp\u003e\n \u003crt\u003e-\u003c/rt\u003e\n \u003crp\u003e)\u003c/rp\u003e\u0026nbsp;\n \u003c/ruby\u003e\u0026plusmn;S, cM(IQR), HR is heart rate, SBP is systolic blood pressure, APACHEII score is acute physiology and chronic health status II score, SOFA score is sequential organ failure score, NT-pro BNP is N-terminal pro-B natriuretic peptide, cTn-l is cardiac troponin I, and NE is norepinephrine dose. LVDd is the left ventricular end-diastolic diameter, ESV is the left ventricular end-systolic volume, SV is the left ventricular stroke volume, LVEF is the left ventricular ejection fraction, LAVI is the left atrial volume index, E/e\u0026apos; is the ratio of the mitral orifice early diastolic peak velocity to the mean of the mitral annulus early diastolic peak velocity, Lateral \u0026nbsp;e is the early diastolic peak velocity of the lateral wall mitral annulus, V\u003csub\u003eTR\u003c/sub\u003e is the tricuspid regurgitation peak velocity, PASP is the pulmonary artery systolic pressure, TAPSE is the tricuspid annulus plane systolic excursion, s\u0026acute; is the tricuspid annulus systolic velocity, GWI is the global work index, GCW is the global constructive work, GWW is the global wasted work, GWE is the global work efficiency, GLS is the global longitudinal strain of the left ventricular, and PSD is the dispersion of the peak time of the global longitudinal strain of the left ventricular. SCM group is septic cardiomyopathy group.\u003c/p\u003e\n\u003cp\u003e2.2 Comparison of clinical and TTE data between survival group and death group:\u003c/p\u003e\n\u003cp\u003eCompared to the survival group, the death group exhibited older age, lower systolic blood pressure (SBP), a higher incidence of septic shock and left ventricular systolic dysfunction (LVSD), elevated Acute Physiology and Chronic Health Evaluation II (APACHE II) and Sequential Organ Failure Assessment (SOFA) scores, and increased levels of N-terminal pro-B-type natriuretic peptide (NT-proBNP), cardiac troponin-I (cTn-I), and norepinephrine dosage. Additionally, the death group had a lower stroke volume (SV),\u0026nbsp;lateral e, tricuspid annular plane systolic excursion (TAPSE), and s\u0026apos;. The differences were statistically significant (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.01).Global work index (GWI) global constructive work (GCW),global work efficiency (GWE), and global longitudinal strain (GLS) were significantly decreased, while peak systolic strain dispersion (PSD) was significantly increased in the death group (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.01). Left ventricular end-diastolic diameter (LVDd) was smaller in the death group compared to the survival group, with a statistically significant difference (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05). However, there was no statistical difference in gender, heart rate (HR), number of supraventricular arrhythmias, end-systolic volume (ESV), left ventricular ejection fraction (LVEF), left atrial volume index (LAVI), E/e\u0026acute; ratio, the peak velocity of tricuspid regurgitation (V\u003csub\u003eTR\u003c/sub\u003e), pulmonary artery systolic pressure (PASP), and global wasted work (GWW) (Table 2).\u003c/p\u003e\n\u003cp\u003eTable 2: Comparison of clinical and TTE data between survival and death group（n=180，\u003cruby\u003e\u0026chi;\u003crp\u003e(\u003c/rp\u003e\n \u003crt\u003e-\u003c/rt\u003e\n \u003crp\u003e)\u003c/rp\u003e\u0026nbsp;\n \u003c/ruby\u003e\u0026plusmn;S）\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eSurvival\u0026nbsp;group(n=135)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003edeath\u0026nbsp;group(n=45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026chi;\u0026sup2;/t\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cem\u003eP value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eGender (male)a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 152px;\"\u003e\n \u003cp\u003e83(61.48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 124px;\"\u003e\n \u003cp\u003e25(55.56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.598\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eAge (years)b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e55.90\u0026plusmn;15.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e64.40\u0026plusmn;12.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e-3.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eHR(beats/min)b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e97.82\u0026plusmn;19.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e107.20\u0026plusmn;29.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e-2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eSupraventricular arrhythmia [case(%)]c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e13(9.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e9(20.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.115\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eSBP(mmHg)b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e123.69\u0026plusmn;20.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e112.47\u0026plusmn;22.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e3.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eCombined shock [cases (%)]c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e70(51.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e34(75.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e6.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eAPACHEⅡ score c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e16.00(7.00）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e20.00(10.00）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1832.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eSOFA score c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e8.00(5.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e11.00(6.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e-2.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eNT-pro BNP(pg/ml)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e1700.00(5927.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e4210.00(9870.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2100.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003ecTn-l(ng/ml)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e0.03(0.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e0.07(0.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2226.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eNE dosage (ug/kg.min）c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e0.10(0.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e0.50(1.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1883.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eLVDd(mm)b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e47.79\u0026plusmn;5.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e45.56\u0026plusmn;6.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eESV(ml)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e35.00(21.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e35.00(32.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e3199.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.593\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eSV(ml)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e65.00(23.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e63.00(24.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e5550.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eLVEF(%)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e66.00(12.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e63.00(24.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e3443.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.180\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eLAVIc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e18.74(8.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e17.90(7.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e3435.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eE/e\u0026acute;c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e9.00(4.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e10.00(5.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2828.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.489\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eLateral e (cm/s)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e10.00(4.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e8.00(3.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e3961.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eV\u003csub\u003eTR\u003c/sub\u003e(m/s)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e2.50(0.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e2.59(0.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2869.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.578\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003ePASP(mmHg)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e30.00(17.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e31.00(15.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2925.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.711\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eTAPSE(mm)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e19.50(5.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e15.00(4.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e4446.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003es\u0026acute;(cm/s)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e14.99\u0026plusmn;4.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e12.22\u0026plusmn;3.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e4.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eMerge LVSD[case (%)]c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 152px;\"\u003e\n \u003cp\u003e63(46.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 124px;\"\u003e\n \u003cp\u003e39(86.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e20.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eGWI(mmHg%)b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e1467.73\u0026plusmn;529.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e973.78\u0026plusmn;541.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e5.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eGCW(mmHg%)b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e1734.05\u0026plusmn;548.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e1241.62\u0026plusmn;579.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e5.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eGWW(mmHg%)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e135.00(129.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e162.00(129.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2508.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eGWE(%)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e91.00(7.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e85.00(13.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e4249.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eGLS(%)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e-15.80(5.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e-12.20(5.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1700.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003ePSD(ms)c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e54.80(26.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e67.20(32.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2132.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote:a case (%),b\u003cruby\u003e\u0026chi;\u003crp\u003e(\u003c/rp\u003e\n \u003crt\u003e-\u003c/rt\u003e\n \u003crp\u003e)\u003c/rp\u003e\u0026nbsp;\n \u003c/ruby\u003e\u0026plusmn;S,cM(IQR),HR is heart rate, SBP is systolic blood pressure, APACHEII score is acute physiology and chronic health status II score, SOFA score is sequential organ failure score, NT-pro BNP is N-terminal pro-B natriuretic peptide, cTn-l is cardiac troponin I, and NE is norepinephrine dose. LVDd is the left ventricular end-diastolic diameter,ESV is the left ventricular end-systolic volume, SV is the left ventricular stroke volume, LVEF is the left ventricular ejection fraction, LAVI is the left atrial volume index, E/e\u0026apos; is the ratio of the mitral orifice early diastolic peak velocity to the mean of the mitral annulus early diastolic peak velocity, Lateral \u0026nbsp; e is the early diastolic peak velocity of the lateral wall mitral annulus, V\u003csub\u003eTR\u003c/sub\u003e is the tricuspid regurgitation peak velocity, PASP is the pulmonary artery systolic pressure, TAPSE is the tricuspid annulus plane systolic excursion, s\u0026acute; is the tricuspid annulus systolic velocity, GWI is the global work index,GCW is the global constructive work,GWW is the global wasted work,GWE is the global work efficiency, GLS is the global longitudinal strain of the left ventricular,PSD is the dispersion of the peak time of the global longitudinal strain of the left ventricular.\u003c/p\u003e\n\u003cp\u003e2.3 Relationship between MWI and SCM-LVSD\u003c/p\u003e\n\u003cp\u003eThe results of the logistic regression model examining the relationship between MWI and SCM-LVSD indicated that, prior to accounting for confounding factors, elevated GWI, GCW, and GWE values were associated with a reduced risk of SCM-LVSD [OR 95% CI: 0.82 (0.76-0.87); 0.84 (0.78-0.89); 0.28 (0.15-0.47)]. After controlling for age, APACHE II score, and NT-pro BNP, the findings remained similar to those without adjustment. Conversely, higher GWW values were linked to an increased risk of SCM-LVSD (OR: 1.29, 95% CI: 0.97-1.74), although this association was not statistically significant (p=0.089). Adjusting for age, APACHE II score, and NT-pro BNP did not alter these results. (Table 3).\u003c/p\u003e\n\u003cp\u003eTable 3 Relationship between MWI and SCM-LVSD (n=180)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"647\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003eindicators \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 151px;\"\u003e\n \u003cp\u003emodel 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003emodel 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003emodel 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003emodel 4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003eOR(95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003eOR(95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eOR(95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eOR(95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49px;\"\u003e\n \u003cp\u003eGWI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.82(0.76-0.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 98px;\"\u003e\n \u003cp\u003e0.80(0.73-0.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0.80(0.74-0.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.81(0.75-0.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49px;\"\u003e\n \u003cp\u003eGCW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.84(0.78-0.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 98px;\"\u003e\n \u003cp\u003e0.81(0.75-0.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0.81(0.75-0.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.83(0.76-0.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49px;\"\u003e\n \u003cp\u003eGWW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e1.29(0.97-1.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.089\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 98px;\"\u003e\n \u003cp\u003e1.16(0.87-1.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.315\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e1.17(0.87-1.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003e0.315\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e1.20(0.89-1.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e0.237\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49px;\"\u003e\n \u003cp\u003eGWE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.28(0.15-0.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 98px;\"\u003e\n \u003cp\u003e0.29(0.16-0.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0.31(0.17-0.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.32(0.18-0.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: Model 1 is an unadjusted logistic regression model; Model 2 adjusts for age; Model 3 adjusts for APACHE II score based on Model 2, and Model 4 adjusts for NT-pro BNP based on Model 3.\u003c/p\u003e\n\u003cp\u003e2.4 Relationship between MWI and prognosis of sepsis patients\u003c/p\u003e\n\u003cp\u003eThe results of the multivariate logistic regression model for predicting 28-day mortality in patients with sepsis indicated that, before accounting for confounding factors, elevated GWI, GCW, and GWE values were associated with a reduced risk of 28-day mortality in sepsis patients [OR (95% CI): 0.83 (0.77-0.90); 0.84 (0.78-0.91); 0.41 (0.26-0.63)]. After adjusting for age, APACHE II score, and NT-pro BNP levels, the findings remained similar to those without adjustment. Conversely, higher GWW values were linked to an increased risk of 28-day mortality in patients with sepsis (OR: 1.20, 95% CI: 0.89-1.61), although this association was not statistically significant (p=0.218). Adjusting for age, APACHE II score, and NT-pro BNP levels did not alter these results. (Refer to Table 4).\u003c/p\u003e\n\u003cp\u003eTable 4 Relationship between MWI and 28-day death\u0026nbsp;(n=180)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"643\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 67px;\"\u003e\n \u003cp\u003eindicators \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 142px;\"\u003e\n \u003cp\u003emodel 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003emodel 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003emodel 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003emodel 4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003eOR(95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003ep value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eOR(95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003ep value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eOR(95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eOR(95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 67px;\"\u003e\n \u003cp\u003eGWI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.83(0.77-0.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 91px;\"\u003e\n \u003cp\u003e0.81(0.74-0.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.84(0.76-0.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.83(0.76-0.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 67px;\"\u003e\n \u003cp\u003eGCW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.84(0.78-0.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 91px;\"\u003e\n \u003cp\u003e0.82(0.75-0.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.85(0.77-0.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.84(0.77-0.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 67px;\"\u003e\n \u003cp\u003eGWW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 92px;\"\u003e\n \u003cp\u003e1.20(0.89-1.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e0.218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 91px;\"\u003e\n \u003cp\u003e1.10(0.80-1.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.553\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e1.10(0.77-1.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.577\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e1.11(0.77-1.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.560\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 67px;\"\u003e\n \u003cp\u003eGWE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.41(0.26-0.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 91px;\"\u003e\n \u003cp\u003e0.42(0.26-0.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.45(0.27-0.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.45(0.27-0.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: Model 1 is an unadjusted logistic regression model; Model 2 adjusts for age; Model 3 adjusts for APACHE II score based on Model 2, and Model 4 adjusts for NT-pro BNP based on Model 3.\u003c/p\u003e\n\u003cp\u003e2.5 Diagnostic efficacy of MWI in SCM-LVSD\u003c/p\u003e\n\u003cp\u003eDiagnostic test results indicated that GWI, GCW, GWW, GWE, LVEF, GLS, cTn-I, and NT-proBNP all possess certain diagnostic value for SCM-LVSD. Among these, GLS exhibits the highest diagnostic efficiency, with an AUC of 0.81, followed by GWI (AUC of 0.77) and GCW (AUC of 0.77), then GWE (AUC of 0.73), and cTn-I (AUC of 0.72). The diagnostic efficiency of LVEF and GWW is relatively poor, with AUCs of 0.67 and 0.61, respectively. (Table 5).\u003c/p\u003e\n\u003cp\u003eTable 5 ROC curve results of MWI indicators in diagnosing SCM-LVSD（n=180，\u003cruby\u003e\u0026chi;\u003crp\u003e(\u003c/rp\u003e\n \u003crt\u003e-\u003c/rt\u003e\n \u003crp\u003e)\u003c/rp\u003e\u0026nbsp;\n \u003c/ruby\u003e\u0026plusmn;S）\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"641\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003eproject\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eAUC\u003c/p\u003e\n \u003cp\u003e（95%CI）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003ecutoff value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003esensitivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003especificity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003eaccuracy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eyouden index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003estandard error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003eGWI(mmHg%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.77(0.71-0.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e1167.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e62.75%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e89.74%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 61px;\"\u003e\n \u003cp\u003e74.17%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 58px;\"\u003e\n \u003cp\u003e1.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003eGCW(mmHg%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.77(0.70-0.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e1640.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e74.51%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e73.08%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 61px;\"\u003e\n \u003cp\u003e73.89%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 58px;\"\u003e\n \u003cp\u003e1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003eGWW(mmHg%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.61(0.53-0.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e130.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e69.61%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e60.26%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 61px;\"\u003e\n \u003cp\u003e63.33%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 58px;\"\u003e\n \u003cp\u003e1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003eGWE(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.73(0.66-0.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e92.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e78.92%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e60.26%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 61px;\"\u003e\n \u003cp\u003e69.44%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 58px;\"\u003e\n \u003cp\u003e1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 117px;\"\u003e\n \u003cp\u003eLVEF(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.67(0.59-0.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e59.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e43.63%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e94.23%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 61px;\"\u003e\n \u003cp\u003e63.89%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 58px;\"\u003e\n \u003cp\u003e1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 117px;\"\u003e\n \u003cp\u003eGLS(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.81(0.75-0.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e-14.95\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e71.57%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e80.77%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 61px;\"\u003e\n \u003cp\u003e75.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 58px;\"\u003e\n \u003cp\u003e1.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 117px;\"\u003e\n \u003cp\u003ecTn-I(ng/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.73(0.66-0.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e80.39%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e64.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 61px;\"\u003e\n \u003cp\u003e72.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 58px;\"\u003e\n \u003cp\u003e1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 117px;\"\u003e\n \u003cp\u003eNT-proBNP(pg/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.72(0.64-0.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e2107.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e72.06%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e71.15%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 61px;\"\u003e\n \u003cp\u003e70.56%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 58px;\"\u003e\n \u003cp\u003e1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: AUC: area under the curve; 95% CI: 95% confidence interval.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.6 Effectiveness of MWI in evaluating the prognosis of patients with sepsis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe diagnostic test results indicated that GWI, GCW, GWW, GWE, LVEF, GLS, cTn-I, and NT-proBNP all possess some prognostic value for predicting 28-day mortality in sepsis patients. \u0026nbsp;GWI exhibited the highest prognostic value with an Area Under the Curve (AUC) of 0.75, followed by GCW (AUC of 0.74), GLS (AUC of 0.72), and GWE (AUC of 0.70). NT-pro BNP (AUC of 0.65) and cTn-I (AUC of 0.63) were also significant, albeit less so. In contrast, GWW and LVEF demonstrated poor prognostic evaluation, with AUCs of 0.59 and 0.57, respectively. (Refer to Table 6).\u003c/p\u003e\n\u003cp\u003eTable 6 Evaluation of MWI on the prognosis of patients with sepsis（n=180，\u003cruby\u003e\u0026chi;\u003crp\u003e(\u003c/rp\u003e\n \u003crt\u003e-\u003c/rt\u003e\n \u003crp\u003e)\u003c/rp\u003e\u0026nbsp;\n \u003c/ruby\u003e\u0026plusmn;S）\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"610\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eproject\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eAUC（95%CI）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003ecutoff value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003esensitivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003especificity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eaccuracy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003eyouden index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003estandard error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eGWI (mmHg%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.75(0.66-0.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1248.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e77.78%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 67px;\"\u003e\n \u003cp\u003e68.52%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 58px;\"\u003e\n \u003cp\u003e71.11%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eGCW (mmHg%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.74(0.66-0.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1600.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e84.44%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 67px;\"\u003e\n \u003cp\u003e60.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 58px;\"\u003e\n \u003cp\u003e66.11%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eGWW (mmHg%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.59(0.49-0.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e130.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e73.33%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 67px;\"\u003e\n \u003cp\u003e51.85%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 58px;\"\u003e\n \u003cp\u003e58.06%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eGWE (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.70(0.61-0.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e85.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e62.22%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 67px;\"\u003e\n \u003cp\u003e76.30%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 58px;\"\u003e\n \u003cp\u003e71.67%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003eLVEF (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.57(0.46-0.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e60.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e50.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 67px;\"\u003e\n \u003cp\u003e75.56%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 58px;\"\u003e\n \u003cp\u003e69.72%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003eGLS (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.72(0.64-0.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-14.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e77.78%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 67px;\"\u003e\n \u003cp\u003e63.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 58px;\"\u003e\n \u003cp\u003e67.78%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003ecTn-I\u0026nbsp;(ng/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.63(0.54-0.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e66.67%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 67px;\"\u003e\n \u003cp\u003e67.04%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 58px;\"\u003e\n \u003cp\u003e68.61%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003eNT-pro BNP (pg/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.65(0.57-0.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1115.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e88.89%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 67px;\"\u003e\n \u003cp\u003e44.81%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 58px;\"\u003e\n \u003cp\u003e56.11%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: AUC: area under the curve; 95% CI: 95% confidence interval.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eSepsis is a prevalent acute and critical illness in medicine and surgery, characterized by high morbidity and mortality rates. The heart is particularly susceptible to sepsis, and the focus of Trans-thoracic echocardiography (TTE) observations is on identifying abnormal cardiac function \u003csup\u003e[12]\u003c/sup\u003e. Sepsis cardiomyopathy (SCM) is acute heart failure caused by sepsis. Of the\u0026nbsp;180 sepsis patients\u0026nbsp;enrolled, 102 exhibited various types of cardiac dysfunction, with a 56.7% incidence of SCM. The left ventricular ejection fraction (LVEF) in the SCM group was 62.00%. It is possible that left ventricular\u0026nbsp;myocardial inhibition was\u0026nbsp;masked by reduced afterload, resulting in a normal LVEF. The diagnostic utility of LVEF for SCM-induced left ventricular systolic dysfunction (LVSD) was found to be low (AUC: 0.67). Previous studies that used an LVEF\u0026lt;50% to diagnose SCM\u003csup\u003e\u0026nbsp;[13, 14]\u003c/sup\u003e led to numerous missed diagnoses. The 28-day mortality rate in this study was 7.7% for the sepsis group and 38.2% for the SCM group. The presence of SCM significantly increased the mortality rate among sepsis patients \u003csup\u003e[15]\u003c/sup\u003e. Early identification of SCM and timely intervention are crucial in reducing sepsis-related deaths. Global longitudinal strain (GLS) can detect more subtle LVSD when LVEF appears normal and is currently the preferred method for studying the relationship between left ventricular systolic function and prognosis in SCM patients \u003csup\u003e[16]\u003c/sup\u003e. In the two grouping methods used in this study, the GLS of the SCM group was significantly lower than that of the sepsis group, and the death group's GLS was lower compared to the survival group, at -12.30%(5.65%) and -12.20%(5.00%) respectively.\u003c/p\u003e\n\u003cp\u003ePatients with sepsis or septic shock who receive systemic vasopressors and rapid fluid resuscitation often experience significant fluctuations in blood pressure. In this study, systolic blood pressure (SBP) differed between the sepsis group and the SCM group, as well as between the survival group and the death group. An increase in afterload leads to a decrease in global longitudinal strain (GLS) values, which can result in clinicians misjudging the true left ventricular (LV) systolic function \u003csup\u003e[17]\u003c/sup\u003e. The myocardial work index (MWI) is a novel method for non-invasively constructing a LV pressure-strain loop (PSL) to quantitatively assess myocardial systolic function. It allows the study of LV systolic function under varying afterload conditions and correlates well with biochemical indicators such as NT-pro BNP for diagnosing cardiac dysfunction \u003csup\u003e[18]\u003c/sup\u003e. The parameters of MWI include global work index (GWI), global constructive work (GCW), global wasted work (GWW), and global work efficiency (GWE). GWI represents the area of the PSL, which corresponds to LV systolic work per stroke; GCW is the work done that facilitates ejection, GWW equals GCW minus GWI, representing the work that does not contribute to ejection; and GWE equals GCW divided by the sum of GCW and GWW, multiplied by 100%, reflecting the efficiency of myocardial work. Both GWI and GCW are considered indicators of the overall efficiency of the LV, and decreases in their values suggest LV systolic dysfunction (LVSD). GWI is closely related to myocardial oxygen consumption, while GCW is secondary \u003csup\u003e[19]\u003c/sup\u003e. The sepsis group in this study (average age 53.29±15.11 years) and the MWI data from a study by Ding Xueyan et al.\u003csup\u003e\u0026nbsp;[20]\u003c/sup\u003e on 64 healthy adult volunteers (average age 52.1±10.7 years) were significantly lower. The analysis suggested that the heart is a high-energy-consuming organ, and under sepsis, the LV faces a conflict between energy supply and demand due to inflammatory storms, metabolic disorders, mitochondrial damage, and pressure stress after norepinephrine (NE) application. Additionally, the early inflammatory response in sepsis leads to decreased sensitivity of cardiomyocytes to Ca2+, mitochondrial dysfunction, and down-regulation of β-adrenergic receptor expression, resulting in myocardial inhibition \u003csup\u003e[21]\u003c/sup\u003e. Compared with the sepsis group, the SCM group showed significantly reduced GWI, GCW, and GWE, and a significantly increased GWW, indicating more increased myocardial energy loss and significant LVSD. The analysis reasons were: (1) SCM patients were older (61.65±14.64 years) than sepsis patients, and increased wall rigidity in elderly patients affects LV filling, while heart rate (HR) is accelerated by systemic inflammatory response syndrome and shortened LV filling time, potentially causing a reduction in stroke volume (SV), GWI, and GCW; (2) The SCM group had an increased pulmonary artery systolic pressure (PASP) of 33mmHg, related to lung injury and hypoxemia caused by infection. A slight increase in PASP can lead to a significant decrease in right ventricular stroke volume, triggering interventricular interactions and causing mechanical asynchrony during the normal cardiac cycle \u003csup\u003e[22]\u003c/sup\u003e. The SCM group also had a prolonged PSD that is a strain parameter used to evaluate LV systolic synchrony. Mechanical asynchrony results in wasted work on the asynchronous diastolic segments \u003csup\u003e[20]\u003c/sup\u003e. A significant increase in GWW will further deteriorate LV pump function \u003csup\u003e[22]\u003c/sup\u003e; (3) The use of high-dose NE may increase afterload after correcting severe distributive shock and myocardial inhibition becomes apparent. Therefore, MWI can detect subclinical LVSD and assist in assessing myocardial efficiency in SCM patients.\u003c/p\u003e\n\u003cp\u003eHedwig et al. \u003csup\u003e[18]\u0026nbsp;\u003c/sup\u003eproposed that a GWI\u0026lt;500mmHg% is a predictor of significant left ventricular (LV) remodeling, severe impairment of left ventricular ejection fraction (LVEF), and a significant increase in N-terminal pro-B-type natriuretic peptide (NT-pro BNP). Chan et al.\u003csup\u003e\u0026nbsp;[19]\u003c/sup\u003e found that significant reductions in GWI and GWE suggested that LV myocardial systolic function in patients with dilated cardiomyopathy was significantly impaired. The results of the Logistic regression model in this study showed that the higher the GWI, GCW, and GWE values, the lower the risk of developing septic cardiomyopathy with left ventricular systolic dysfunction (SCM-LVSD), and the higher the GWW value, the higher the risk of developing SCM-LVSD; global longitudinal strain (GLS) has the highest diagnostic power for SCM-LVSD, with an area under the curve (AUC) of 0.81, followed by GWI (AUC of 0.77) and GCW (AUC of 0.77), and then by GWE (AUC of 0.73), cardiac troponin I (cTn-I) (AUC of 0.73), and NT-pro BNP (AUC of 0.72). The diagnostic power of LVEF and GWW is poor. The presence of LVSD had significant predictive value for 28-day mortality in sepsis patients. Logistic regression model results showed that the higher the GWI, GCW, and GWE values, the lower the risk of 28-day mortality in sepsis patients. The highest prognostic value for 28-day mortality in sepsis patients was GWI with an AUC of 0.75, followed by GCW (AUC of 0.74), GLS (AUC of 0.72), and GWE (AUC of 0.70), and then by NT-pro BNP (AUC of 0.65) and cTn-I (AUC of 0.63); the prognostic evaluation effect of GWW and LVEF is poor.\u003c/p\u003e\n\u003cp\u003eSCM refers to a form of heart failure caused by energy deficit in the heart due to sepsis, essentially characterized by reduced cardiac work efficiency. As a novel technique for evaluating left ventricular (LV) myocardial contraction efficiency, Myocardial Work Index (MWI) enables clinicians to better understand LV systolic performance under different afterload conditions [23]. It accurately reflects myocardial oxygen consumption and can be regarded as a comprehensive and powerful tool for assessing LV systolic function and predicting prognosis in sepsis patients.\u003c/p\u003e\n\u003cp\u003eThis study has several limitations: First, as a single-center prospective cohort study, the relatively small sample size may diminish statistical power and impact the generalizability of the study's conclusions; second, the current diagnosis of septic cardiomyopathy (SCM) lacks internationally recognized diagnostic criteria, which may result in selection bias and classification heterogeneity. At the methodological level, although core ultrasound indicators such as left and right ventricular function were systematically evaluated, a multiple organ dysfunction assessment system was not integrated, which may affect the comprehensive judgment of clinical phenotypes. Additionally, some patients had received positive inotropic medication intervention before echocardiography examination, and while stratified analysis was used, there may still be residual confounding factors that were not fully controlled. Therefore, further prospective large-sample, multi-center studies are still needed to clarify the evaluative and prognostic roles of MWI in SCM-LVSD.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eConflict of interest:\u003c/h2\u003e\u003cp\u003e\u003cem\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/em\u003e\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eXu Yanping : collect data and write paperYang Xiaojuan :subject design and application for fundWu Jiali:methodology and statisticsYang Xue ,Pan Lu,Yang Ying, Wang Ying and Cao Wei:project implementation and measurementWang Xiaohong and Na Lisha:supervision\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eEvansA L. RhodesW. AlhazzaniM. M. LevyM. AntonelliR. FerrerA. KumarJ. E. 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Chin J Electron Crit Care Med. 2020;6(2):128\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCheng Xiansheng. Interdependence of Ventricles and Mechanical Function Patterns of Right Heart Myocardium. [J]. Chin J Cardiovasc Dis. 2020;48(10):814\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFan Jingdong L, Min S. Advances in the Application of Ultrasound Myocardial Work Technique in Evaluating Left Ventricular Dysfunction Due to Different Etiologies. [J]. J Clin Ultrasound Med. 2023;25(2):137\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cardiovascular-ultrasound","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"caru","sideBox":"Learn more about [Cardiovascular Ultrasound](http://cardiovascularultrasound.biomedcentral.com/)","snPcode":"12947","submissionUrl":"https://submission.nature.com/new-submission/12947/3","title":"Cardiovascular Ultrasound","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Myocardial work indexes, Sepsis, Septic cardiomyopathy, Left ventricular Systolic dysfunction, Ejection fraction, Global longitudinal strain","lastPublishedDoi":"10.21203/rs.3.rs-7179383/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7179383/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e: This study was to determine whether myocardial work indexes (MWI) could quantitatively assess left ventricular systolic dysfunction in patients with septic cardiomyopathy (SCM-LVSD) and their predictive efficacy for prognosis in sepsis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: Based on the echocardiographic performance of the left and/or the right ventricular dysfunction, 180 enrolled sepsis were categorized into two groups: the sepsis group and the septic cardiomyopathy (SCM)group . Additionally, the survival group and the mortality group based on their prognosis at 28 days post-admission. Univariate and multivariate logistic regression analyses were performed to explore the relationship between MWI, SCM-LVSD, and prognosis. The diagnostic efficacy of MWI in identifying SCM-LVSD was evaluated using diagnostic tests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResult: \u003c/strong\u003e① MWI parameters Comparison: The global work index (GWI), global constructive work (GCW), and global work efficiency (GWE) were significantly reduced in the SCM and mortality groups versus controls (all \u003cem\u003eP\u003c/em\u003e\u0026lt;0.01). While, the global wasted work (GWW) was significantly higher in the SCM group than in the sepsis group (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.01). ② Comparison of the diagnostic efficacy in identifying SCM-LVSD: The global longitudinal strain (GLS) demonstrated the highest diagnostic value (area under the receiver operating characteristic curve [AUCs= 0.81], followed by GWI and GCW (AUC=0.77 each)，and GWE (AUC=0.73), the left ventricular ejection fraction (LVEF) and the GWW exhibited lower diagnostic efficacy. ③ Comparison of the prognostic value: GWI, GCW, GLS, and GWE showed the best predictive efficacy for adverse prognosis (AUC of 0.75, 0.74, 0.72, and 0.70, respectively), whereas GWW and LVEF showed limited value.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: MWI could more accurately quantify the SCM-LVSD. GLS, GWI, and GCW demonstrated higher diagnostic efficacy. Additionally, GWI, GCW, and GWE provided valuable prognostic efficacy for 28-day mortality in sepsis. MWI serves as a valuable tool for the early identification of SCM-LVSD and prognostic assessment of sepsis.\u003c/p\u003e","manuscriptTitle":"Quantitative Assessment and Prognostic Value of Myocardial Work Indexes in Septic Cardiomyopathy Patients with Left Ventricular Systolic Dysfunction","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-14 09:56:50","doi":"10.21203/rs.3.rs-7179383/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-27T01:31:04+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-22T15:12:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"205658225076692759443275133695433181445","date":"2025-09-29T08:09:55+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-27T16:10:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"207938507213591831497328206404540582345","date":"2025-09-23T06:50:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"269967296947141386928860660058112326309","date":"2025-08-20T18:04:02+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-07T17:38:34+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-22T00:34:51+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-22T00:33:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cardiovascular Ultrasound","date":"2025-07-21T15:54:49+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cardiovascular-ultrasound","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"caru","sideBox":"Learn more about [Cardiovascular Ultrasound](http://cardiovascularultrasound.biomedcentral.com/)","snPcode":"12947","submissionUrl":"https://submission.nature.com/new-submission/12947/3","title":"Cardiovascular Ultrasound","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"82f18ae4-ce73-4dba-8e0b-d163e4858b54","owner":[],"postedDate":"August 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-04-13T16:14:45+00:00","versionOfRecord":{"articleIdentity":"rs-7179383","link":"https://doi.org/10.1186/s12947-026-00370-w","journal":{"identity":"cardiovascular-ultrasound","isVorOnly":false,"title":"Cardiovascular Ultrasound"},"publishedOn":"2026-04-06 15:57:21","publishedOnDateReadable":"April 6th, 2026"},"versionCreatedAt":"2025-08-14 09:56:50","video":"","vorDoi":"10.1186/s12947-026-00370-w","vorDoiUrl":"https://doi.org/10.1186/s12947-026-00370-w","workflowStages":[]},"version":"v1","identity":"rs-7179383","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7179383","identity":"rs-7179383","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}