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 Table of Contents  
ORIGINAL ARTICLE
Year : 2018  |  Volume : 5  |  Issue : 3  |  Page : 178-186

Left-ventricular global longitudinal systolic strain and strain rate can predict sepsis outcome: comparison between speckle-tracking echocardiography and tissue-Doppler imaging


Critical Care Medicine Department, Faculty of Medicine, Cairo University, Cairo, Egypt

Date of Submission08-Feb-2017
Date of Acceptance06-Nov-2017
Date of Web Publication31-Aug-2018

Correspondence Address:
Hossam M Sherif
Critical Care Center, Cairo University Hospitals, El Manial, Cairo, 11562
Egypt
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/roaic.roaic_20_17

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  Abstract 

Background Strain imaging, by either tissue-Doppler imaging (TDI) velocity converted to strain or strain rate or by two-dimensional speckle-tracking echocardiography (STE) analysis, is used to evaluate abnormal left-ventricular (LV) mechanical activation patterns in sepsis.
Objective The aim of this study was to predict sepsis outcomes using LV strain and strain-rate measurements as well as to establish a comparison between STE and TDI.
Patients and methods This study included 32 patients (43.7±13.7 years, 21 males) [13 patients with sepsis (group 1) and 19 patients with severe sepsis/septic shock (group 2)] and a subset of 10 controls (36.5±8.7 years, eight males). In the first 24 h, color-TDI was performed for LV 16 segments, and Doppler flow profiles were reanalyzed using STE to retrieve LV peak global longitudinal systolic strain (GLSS) and global longitudinal systolic strain rate (GLSSR), which were averaged for the whole segment.
Results Compared with the controls, ejection fraction (%EF) of both groups were comparable, but GLSS showed increased values (−17.5±2.9 vs. −20.2±1.6%, P<0.05 by STE; and −14.9±2.6 vs. −19.7±1.8%, P<0.001 by TDI) and for GLSSR values (−1.3±0.2 vs. −1.6±0.1 s−1, P<0.001 by STE, and −1.1±0.4 vs. −1.6±0.1 s−1, P<0.001 by TDI). Compared with group 1, GLSS of group 2 showed increased values (−15.4±1.5 vs. −20.2±2.4%, P<0.05 by STE; and −12.7±6.8 vs. −18.1±2.4%, P<0.05 by TDI). A good correlation was detected between Acute Physiology and Chronic Health Evaluation II score and either GLSS-STE or GLSSR-STE (r=0.88, P<0.001; and r=0.54, P<0.05) and a moderate correlation was detected between %EF and either GLSS-STE or GLSSR-STE (r=0.47, P<0.05; and r=0.45, P<0.05). The area under the curve of GLSS-STE to predict mortality was 0.9 (95% confidence interval: 0.32–0.48), with best cutoff value at −16.8% (sensitivity: 100%, specificity: 86%), and the area under the curve for GLSS-TDI was 0.76% (95% confidence interval: 0.1–0.44), with best cutoff value at −14.9 (sensitivity: 100%, specificity: 82%).
Conclusion LV GLSS and GLSSR obtained using STE were more specific and showed a better correlation with both Acute Physiology and Chronic Health Evaluation II and %EF rather than TDI in predicting mortality.

Keywords: left-ventricular strain, left-ventricular strain rate, sepsis, speckle-tracking, tissue-Doppler imaging


How to cite this article:
Hassanin H, Sherif HM, Al Hossainy R, Sami W. Left-ventricular global longitudinal systolic strain and strain rate can predict sepsis outcome: comparison between speckle-tracking echocardiography and tissue-Doppler imaging. Res Opin Anesth Intensive Care 2018;5:178-86

How to cite this URL:
Hassanin H, Sherif HM, Al Hossainy R, Sami W. Left-ventricular global longitudinal systolic strain and strain rate can predict sepsis outcome: comparison between speckle-tracking echocardiography and tissue-Doppler imaging. Res Opin Anesth Intensive Care [serial online] 2018 [cited 2018 Nov 12];5:178-86. Available from: http://www.roaic.eg.net/text.asp?2018/5/3/178/240265


  Introduction Top


Sepsis remains one of the most common causes of hospitalization, and despite recent significant therapeutic advances, the mortality rate of critically ill patients with sepsis remains high [1]. Many septic patients admitted to the ICU do not express any early clinical signs or symptoms reflecting myocardial injury, but up to 85% of them show cardiac involvement in a later stage, which would be associated with increased hospital mortality [2]. A proportion of patients who suffer from sepsis also exhibits left-ventricular (LV) systolic dysfunction, which is easily underdiagnosed clinically or using the conventional echocardiography tools for evaluation [3].

Owing mainly to its semiquantitative nature and inability to detect subclinical cardiac dysfunction, conventional echocardiography has several major limitations in assessing LV systolic function [4]. Various echocardiographic parameters have been developed for better assessment of systolic LV function. Although ejection fraction (%EF) is the most commonly used parameter for evaluating LV systolic function, it gives conflicting results for clinical outcome in high-risk patients, especially in those with septic shock [5].

The analysis of myocardial deformation has recently emerged as a quantitative means for reliably estimating myocardial contractility [6]. The strain represents the shortening percentage of the myocardial fibers, whereas the strain rate represents the speed of myocardial deformation, which is derived as a function of both strain and time [6].

The LV strain and strain rate subtracts motion due to the effects of LV neighboring segments, which is known as ‘tethering effect’ [7]. This tethering effect masked both LV pathological deformation and the pathological motion to the normal segments so that the deformation imaging was necessary to locate and show a genuine extent of the pathology and in some situations to exclude the regional pathology [7]. This means that the motion parameters (displacement and velocity) reflect LV global function, whereas the deformation imaging (strain and strain rate) shows the regional function of the myocardium [7].

Recently, two methods have emerged for assessing myocardial deformation: the tissue-Doppler imaging (TDI) velocity converted to strain and strain rate and the digital two-dimensional speckle-tracking echocardiography (STE) analysis [6]. The latter is not based on routine Doppler analysis, but on following or tracing of bright or speckling points through a gray scale analysis [6], which makes it less dependent on the beam angle by estimating strains based on the principal stretches and their corresponding principal axes [8].

It is now well established that not only LV peak global longitudinal systolic strain (GLSS) is more sensitive than the conventional two-dimensional echocardiography (2DE)-derived %EF in detecting LV systolic dysfunction [9] but also it is superior to %EF in the prediction of the main cardiovascular events [9].

Unfortunately, in ICU setting, data are scarce. In both experimental models and human studies on septic shock, STE suggested that GLSS is impaired with preserved %EF. Recent data suggested that impaired GLSS could predict ICU mortality in septic shock [9].

The aim of this study was to compare both TDI and two-dimensional STE techniques in predicting mortality in septic patients as well as to assess LV systolic dysfunction, which could be missed by the conventional echocardiography parameters in such patients, using both LV peak GLSS and LV peak global longitudinal systolic strain rate (GLSSR).


  Patients and methods Top


This was a prospective observational study including 32 patients and a subset of 10 controls. The patients were admitted either to Critical Care Medicine Department, Cairo University Hospitals, or to Bab-El Shearea University Hospital, Al-Azhar University, Egypt.

This investigation was approved by the Ethical Committee Review Board of both the Faculty of Medicine, Cairo University, and Faculty of Medicine, Al-Azhar University. Informed written consent was acquired from each patient before the enrollment in the study.

Inclusion criteria

Any patient who suffered from either sepsis, severe sepsis, or septic shock during 24 h after ICU admission were included in the study.

Criteria for diagnosis of sepsis, severe sepsis, and septic shock included the following [10]:

Systemic inflammatory response syndrome

Two or more of the following:
  1. Body temperature more than 38.5°C or less than 35.0°C.
  2. Heart rate more than 90 beats/min.
  3. Respiratory rate more than 20 breaths/min, or arterial CO2 tension less than 32 mmHg, or a need for mechanical ventilation.
  4. White blood cell count more than 12 000/mm3 or less than 4000/mm3 or immature forms more than 10%.


Sepsis

Systemic inflammatory response syndrome and documented infection (culture or Gram stain of blood, sputum, urine, or normally sterile body fluid positive for pathogenic microorganism; or focus of infection identified by visual inspection, e.g. ruptured bowel with free air or bowel contents found in abdomen at surgery or wound with purulent discharge).

Severe sepsis

Sepsis and at least one sign of organ hypoperfusion or organ dysfunction:
  1. Areas of mottled skin.
  2. Capillary refilling time 3 s or more.
  3. Urinary output less than 0.5 ml/kg for at least 1 h or renal replacement therapy.
  4. Lactate levels more than 2 mmol/l.
  5. Abrupt change in mental status or abnormal ECG.
  6. Platelet counts less than 100 000 ml−1 or disseminated intravascular coagulation.
  7. Acute lung injury/acute respiratory distress syndrome.
  8. Evidence of cardiac dysfunction in echocardiography.


Septic shock

Severe sepsis and one of the following:
  1. Systemic mean blood pressure 60 mmHg (80 mmHg if previous hypertension) after 20–30 ml/kg starch or 40–60 ml/kg serum saline, or pulmonary capillary wedge pressure between 12 and 20 mmHg.
  2. Need for dopamine more than 5 μg/kg/min or norepinephrine or epinephrine less than 0.25 μg/kg/min to maintain mean blood pressure above 60 mmHg (80 mmHg if previous hypertension).


Patients who had ischemic heart disease, arrhythmias especially atrial fibrillation, patients who showed significant valvular, myocardial, or pericardial diseases were excluded from the study. We also excluded patients who showed poor echocardiographic windows and for whom complete echocardiographic study was not feasible.

All the patients were subjected to the following:
  1. Full clinical evaluation.
  2. 12-Lead ECG.
  3. Calculation of Acute Physiology and Chronic Health Evaluation II (APACHE II) score [11]:
    • APACHE II score was designed to measure the severity of disease for adult patients admitted to ICU. It was applied within 24 h of ICU admission based on several measurements; higher scores correspond to more severe disease and a higher risk of death.
    • APACHE II score was calculated using the routine 12 physiological measurements including age, rectal temperature, mean arterial pressure, arterial pH, heart rate, respiratory rate, serum sodium, serum potassium, creatinine, hematocrit, white blood cell count, and Glasgow coma scale.
  4. Baseline transthoracic echocardiography:
    • Each patient was examined in the first 24 h after ICU admission by an experienced echocardiographer in the left lateral decubitus position following the American Society of Echocardiography recommendations. Images were acquired from each part of the examination sequence together with lead-II of ECG and were stored on videotape for subsequent offline cine-loop analysis [12].
    • Apparatus:
    • We used a Philips IE33 (Philips Medical Systems, Andover, Massachusetts, USA) colored echocardiography machine with a 3.5 MHz transducer available in both Critical Care Center, Cairo University Hospitals, and Bab-El Shearea University Hospital, Al-Azhar University, Egypt, to record 2DE and M-mode in the three classic views: long, short parasternal, and apical views.
    • Evaluation of conventional left-ventricular systolic function[12]:
      1. 2DE was performed in the standard three views for the assessment of LV global and regional contractility:
        1. Parasternal long axis view.
        2. Parasternal short axis view at different levels (great vessels, LV at mitral valve leaflets, and papillary muscles).
        3. Apical views: four-chamber (4CH), five-chamber (5CH), and two-chamber (2CH) views.
      2. M-Mode:
        • Under the guidance of 2DE, using the parasternal views, M-mode cursor was positioned at the level of the mitral valve leaflets tips to measure the following:
          1. The left-ventricular end-systolic dimension (LVESd) and left-ventricular end-diastolic dimension (LVEDd) were measured at the end of T-wave and R-wave of the ECG, respectively.
          2. The left-ventricular fractional shortening percentage was calculated as: [(LVEDd–LVESd)/LVEDd]×100.
          3. The LV %EF: systolic dysfunction was defined as %EF below 55%, which was automatically calculated by the machine software.
    • Evaluation of left-ventricular segmental and peak global longitudinal systolic strain and strain rate using the following:
      1. Digital two-dimensional speckle-tracking echocardiography analysis [6],[7]:
        • The speckle-tracking analysis was performed offline for each image using the automated software products: QLAB 9- Cardiac Motion Quantification (CMQ) for both STE and TDI analysis for Strain Quantification in all LV apical views (4CH, 5CH, and 2CH views). For each LV apical view, three sampling points were placed manually at the septal and lateral mitral annulus and at the apical endocardium. A region of interest (ROI) was then generated automatically by the software to cover the entire thickness of LV myocardium. ROI was adjusted manually to provide optimal tracking. GLSS (in percentage) was obtained from one representative cycle, avoiding premature LV beats. We chose to analyze the cardiac cycle with the best tracking and visually most satisfactory strain curves and assessed the tracking quality, and corrections were made if necessary. The offline analysis was made by two experienced investigators blinded to the patient’s underlying characteristics.
        • For evaluation of LV segmental longitudinal systolic strain values, we followed the American Society of Echocardiography’s 17-segment LV model in each apical view [12], and the values were generated automatically. For better comparison, we excluded LV apex from our study.
        • GLSS (in percentage) was calculated as an average of all segmental strains; the results of all three apical planes were represented in one single bull’s-eye summary as peak segmental and global strains generated by CMQ model for LV 16-segment model.
        • GLSSR (in s−1) was calculated as an average of all LV segmental strain rates. CMQ software enabled us to obtain the segmental strain-rate parameters and the segmental strain-rate curves.
      2. TDI velocity converted to strain and strain-rate analysis [7]:
        • For TDI strain analysis, first we acquired TDI image using a frame rate more than 100 frames/s to resolve the regional velocities and to calculate Strain Quantification. TDI analysis was performed for each image in the three LV apical views using the same automated CMQ software product.
        • In each LV apical view, ROI was placed within the interventricular septum and LV wall, and then it was determined manually with a width of 0.5 cm and a length of 1–1.8 cm for each 16 myocardial segment.
        • The software program allowed manual frame-by-frame adjustment of the position of the sample volume to track the proper ROI throughout the cardiac cycle.
        • After determination of ROI manually, GLSS and GLSSR values could be obtained from the strain and strain-rate curves of each myocardial segment, then the segmental parameters were averaged to obtain LV global strain and strain rate.
  5. A standard case report form was used for every patient to record daily progression by reviewing medical records until 30 days or death. All patients were followed up for the length of ICU stay and the outcome.


Statistical analysis

Data were described as mean±SD, range, frequency (number of cases), and percentages when appropriate. Statistical package for the social sciences (SPSS, version 14.0; SPSS Inc., Chicago, Illinois, USA) was used for statistical analysis. Comparisons between groups were made using nonparametric Kruskal–Wallis test or Mann–Whitney test. For comparing serial measurements, the nonparametric Friedman test or Wilcoxon test was used. For comparing categorical data, χ2-test was performed. The analysis of variance test was used for analyzing the differences among multiple groups’ means. Correlations between variables were determined using Spearman’s correlation coefficient. Receiver operator characteristic curves were derived, and area under the curve (AUC) analysis was performed to get the best cutoff values. P values of less than 0.05 were considered as statistically significant.


  Results Top


This study was conducted on 32 critically ill patients (43.7±13.7 years, 21 males) and 10 individuals were included as controls (36.5±8.7 years, eight males).

The patients were segregated into:
  • Group 1: 13 patients with sepsis.
  • Group 2: 19 patients with severe sepsis/septic shock.


[Table 1] shows demographic and clinical data of the patients of both groups, and [Table 2] shows etiology of sepsis in all patients.
Table 1 Demographic and clinical and data

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Table 2 Etiology of sepsis

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Echocardiographic data

  • Assessment of LV global contractility using M-mode ([Table 3]):
    • The data showed comparable results between both patients and controls, but compared with group 1, %EF of group 2 showed statistically significant reduced values (P<0.05).
    Table 3 M-mode echocardiography data

    Click here to view
  • Assessment of LV strain and strain rate using STE and TDI ([Table 4]):
    • The data showed comparable results using both techniques of STE and TDI and comparable results between patients in group 1 and the controls for both GLSS and GLSSR.
    Table 4 Strain and strain-rate data

    Click here to view


However, on estimating the differences among patients in group 2 and controls, GLSS of group 2 obtained by either STE or TDI showed statistically significant increased values (P<0.05 and <0.001, respectively) and GLSSR obtained by either STE or TDI of group 2 also showed statistically significant increased values (P<0.001 and <0.001, respectively).

Compared with group 1, GLSS of group 2 obtained by either STE or TDI showed statistically significant increased values (P<0.05 and <0.05), but the data were comparable during estimation of GLSSR obtained by either STE or TDI.

A moderate correlation could be detected between %EF and either GLSS-STE or GLSSR-STE values ([Figure 1]), but with TDI the correlation was poor.
Figure 1 Correlation between (a) %EF and GLSS-STE, and (b) GLSSR-STE.

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Acute Physiology and Chronic Health Evaluation II score data

Compared with group 1, patients in group 2 showed statistically significant higher APACHE II scores (20.5±5.3 vs. 10.2±2.2, P<0.001).

A good correlation could be detected between APACHE II score and either GLSS-STE or GLSSR-STE values ([Figure 2]), but with TDI the correlation was poor.
Figure 2 Correlation between (a) APACHE II score and GLSS-STE, and (b) GLSSR-STE.

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The intensive care unit mortality

The total mortality was 26.3% at 30 days; all in group 2 (n=10).

Compared with the survivors, the nonsurvivors showed higher APACHE II scores (13.1±4.2 vs. 23.5±5.4, P<0.001), but %EF values were comparable.

Compared with the survivors, the nonsurvivors showed statistically significant increase in GLSS either obtained by STE or TDI (P<0.05 and <0.001, respectively) ([Figure 3]). The same findings also could be detected on comparing survivors with nonsurvivors; they showed statistically significant increase in GLSSR either obtained by STE or TDI (P<0.001 and <0.001, respectively) ([Figure 3]).
Figure 3 (a) GLSS and (b) GLSSR in survivors and non-survivors using STE and TDI.

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For the prediction of ICU mortality in all patients, receiver operator characteristic curves were generated on day 1 for GLSS-STE [AUC=0.9, 95% confidence interval (CI): 0.32–0.48, with best cutoff value at −16.8] and GLSS-TDI (AUC=0.76, 95% CI: 0.1–0.44, with best cutoff value at −14.9) ([Figure 4]).
Figure 4 ROC curve showing the best cutoff values of GLSS and GLSSR for prediction of ICU mortality.

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For GLSSR-STE to predict mortality at day 1, AUC was 0.96 (95% CI: 0.1–0.45), with best cutoff value at −1.2; and for GLSSR-TDI to predict mortality at day 1, AUC of was 0.92 (95% CI: 0.35–0.49), with best cutoff value at −1.2 ([Figure 4]).

Both STE and TDI showed a sensitive prediction of mortality in sepsis, but STE approach was more specific ([Table 5]).
Table 5 Best cutoff values, sensitivities and specificities of speckle-tracking echocardiography and tissue-Doppler imaging

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  Discussion Top


We studied 32 patients admitted to ICU with sepsis. Compared with patients in group 1, patients in group 2 were comparable in LV volumes. These findings are in agreement with those of Furian et al. [13], who demonstrated that sepsis-induced vasodilatation might mask early myocardial dysfunction with reduced afterload. Therefore, LV volumes might not be affected and could not be fully reflecting the myocardial dysfunction.

Our results showed comparable %EF values for group 1 and controls, but patients in group 2 showed statistically significant lower values, despite still preserved %EF (>50%). These findings were in agreement with the landmark study by Parker et al. [14], who first described cardiac dysfunction in septic shock patients and showed systolic impairment in only 10 out of 20 patients during the first 48 h of ICU admission. However, a later study done by Pulido et al. [15] have reported similar results with a reduced global systolic function in septic shock patients, but those who survived showed reversibility. Also, Orde et al. [16] studied 60 patients with severe sepsis and septic shock and found that 40 patients (66.6%) had preserved %EF, as well as Dalla et al. [17], who studied 48 patients with severe sepsis and septic shock, found that 34 (70%) patients had preserved %EF.

Our results showed equal variances between patients of group 1 and controls as regard to LV strain and strain-rate evaluation using both techniques of STE and TDI. However, compared with the controls, patients in group 2 showed statistically significantly increased values of GLSS and GLSSR by either STE or TDI. These findings reflected that the patients with sepsis showed normal systolic cardiac function because of preserved LV volumes, but patients with more severe types of sepsis (severe sepsis/septic shock) showed systolic cardiac dysfunction. Our findings are in agreement with the results of Shahul et al. [17], who studied 15 patients with sepsis and 35 patients with septic shock and found that LV longitudinal strain percentage worsened significantly in patients with septic shock rather than sepsis alone, despite preserved %EF in all patients.

These findings also agreed with those of de Geer et al. [18], who showed a preserved %EF when LV global longitudinal peak strain was altered. In agreement with our data, Dalla et al. [19], who studied 48 patients with severe sepsis/septic shock, found that in septic patients with preserved %EF (>50%, N=34), 17 (50%) patients had a depressed LV global longitudinal function (LV global strain>15%), compared with two (8.7%) patients in the nonseptic group (P<0.05). Similar findings were also noticed by Landesberg et al. [20], who found a severe LV longitudinal strain impairment with preserved %EF in 106 adult patients with septic shock. Orde et al. [15] also concluded that LV longitudinal strain unmasked LV systolic dysfunction unrecognized with conventional echocardiography in patients with severe sepsis or septic shock.

In contrast, our results showed a moderate correlation between %EF and either GLSS-STE or GLSSR-STE values, but with TDI the correlation was poor. Brown et al. [21] demonstrated a good correlation between LV longitudinal strain and %EF; they concluded that LV longitudinal strain provided a quantitative myocardial deformation analysis of each LV segment, allowing for early systolic dysfunction detected in patients with preserved %EF. De Geer et al. [18] also demonstrated that LV longitudinal strain correlated with %EF (r=−0.7, P<0.001).

For the clinical scoring data, our study showed statistically significantly higher APACHE II score in patients of group 2 compared with the patient of group 1, reflecting its importance as a clinical score for predicting morbidity. This finding agreed with that of Rangel-Frausto et al. [22] who studied 2527 ICU patients (surgical, medical, and cardiovascular) and found that there was a stepwise increase in mortality as patients moved along systemic inflammatory response syndrome, sepsis, severe sepsis, and septic shock continuum from 7, 16, 20, to 46%, respectively. These results also agreed with those of Chiavone et al. [23], who stated that APACHE II score prognostic index was useful in stratifying patients according to the severity of their health condition. Chang et al. [24] studied 111 ICU patients with septic shock and found that nonsurvivors had statistically significantly higher APACHE II score compared with survivors (23.9 vs. 19.4, P<0.05).

A good correlation could be detected in our study between APACHE II score and either GLSS-STE or GLSSR-STE values, but with TDI the correlation was poor. These results were in agreement with those of Shahul et al. [17], who found that patients with reduced longitudinal strain by STE were more severely ill. Our results showed poor correlation between APACHE II score and either GLSS-TDI or GLSSR-TDI values, but we did not find previous studies discussing this correlation in such type of patients.

In our study, compared with the survivors the nonsurvivors showed statistically significant increase in both GLSS and GLSSR values whether obtained by STE or TDI, reflecting the worse LV systolic functions. These finding were in agreement with those of Cinotti et al. [9], who found that, in septic shock, GLSS obtained by STE showed deteriorated values with preserved %EF, and these data could predict ICU mortality in such patients.

For prediction of ICU mortality in our study, GLSS-STE evaluation on day 1 could predict the mortality with best cutoff value at −16.8% (sensitivity: 100% and specificity: 86%), and for GLSS-TDI the best cutoff value was at −14.9 (sensitivity: 100% and specificity: 82%). The LV longitudinal global strain could independently be associated with mortality in severe sepsis or septic shock patients in our study. These results were in agreement with those of Chang et al. [24] who studied 111 ICU patients with septic shock and found that the nonsurvivors showed increased GLSS values compared with survivors (−11.8 vs. −15%, P<0.001), and to predict mortality, they could set a cutoff value of GLSS at −13% or less.

To our knowledge, this was the first study to compare STE and TDI techniques in sepsis patients, hence, we could not reliably compare our data with other similar studies [Figure 5].
Figure 5 LV apical 4-chamber view showing ROI drawing within the interventricular septum and LV.

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  Limitations Top


The small number of patients in our study made the prognostic value of GLSS and GLSSR in septic patients to be further confirmed in a larger-scale study. We did not perform serial echocardiography for our patients; a longitudinal echocardiography study may provide more information about the clinical progression of sepsis. The LV diastolic function was not evaluated in this study either by conventional echocardiography or deformation parameters, which could give more summative and formative data.


  Conclusion Top


Measurement of LV GLSS and strain rates can unmask LV systolic cardiac dysfunction complicating sepsis rather than the conventional echocardiography.

STE showed a better correlation with both APACHE II and %EF than TDI; hence, measurement of LV strain and strain rates adds prognostic information to APACHE II score and allows for early identification of high-risk septic patients. Both techniques showed a sensitive prediction of mortality in sepsis, but STE approach was more specific.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

 
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    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]



 

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Abstract
Introduction
Patients and methods
Results
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