Shock index, modified shock index, and age-adjusted shock index for the prediction of impaired myocardial work in patients with ST-segment elevation myocardial infarction

Introduction

Acute ST-segment elevation myocardial infarction (STEMI) is characterized by complete coronary artery occlusion, which leads to sustained myocardial ischemia and necrosis and is often accompanied by hemodynamic instability and impaired cardiac function. Although left ventricular ejection fraction (LVEF) remains a cornerstone of systolic function assessment, it is notably limited by its load dependence, often leading to misinterpretation in acute conditions such as STEMI where hemodynamic status is volatile (1,2). Myocardial work indices, derived from pressure-strain loops, overcome this limitation by incorporating noninvasive blood pressure measurements, thus providing a more accurate assessment of intrinsic myocardial performance that is less influenced by afterload (3,4). Myocardial work indices include global longitudinal strain (GLS), global work index (GWI), global constructive work (GCW), and global work efficiency (GWE), all of which are pivotal in quantifying cardiac energy metabolism and mechanical function, especially subclinical cardiac dysfunction (3,4). However, their measurement relies on specialized high-end echocardiography systems and advanced echocardiographic techniques, limiting accessibility in emergency or resource-limited primary healthcare settings. Thus, identifying a rapid, noninvasive, and easily accessible predictor is crucial for the early identification of high-risk patients and optimizing clinical decision-making.

The shock index (SI), a readily accessible bedside metric, is calculated as the ratio of heart rate to systolic blood pressure (SBP). Originally developed to assess hemorrhagic shock and acute circulatory collapse (5,6), SI has emerged as a valuable tool for rapid risk stratification in acute myocardial infarction. Previous research has established the prognostic utility of SI in STEMI, demonstrating its value as a predictive marker for short-term mortality (7,8), long-term mortality (9-11), microvascular dysfunction (10), and infarct extent (12) among patients treated with percutaneous coronary intervention (PCI). To enhance prognostic accuracy, two SI-derived indices have been proposed: the modified shock index (MSI), computed as heart rate divided by mean arterial pressure (MAP) (8,13); and the age-adjusted shock index (ASI), derived by multiplying SI by patient age (14). The primary advantage of SI and its derivatives in emergency triage is their simplicity and immediacy. They are calculated from vital signs—heart rate and blood pressure—that are universally and rapidly obtainable. This reliance on readily available data allows for early risk stratification even before comprehensive echocardiography or invasive monitoring can be performed (15). However, the association between SI and impaired myocardial work indices has not been systematically investigated. Theoretically, elevated SI may impair myocardial function via two potential pathways: first, tachycardia increases myocardial oxygen consumption, while hypotension reduces coronary perfusion, collectively exacerbating myocardial ischemia; second, neurohormonal activation (e.g., sympathetic overdrive) may accelerate adverse myocardial remodeling, leading to diminished mechanical efficiency.

This study aimed to validate the predictive value of SI and its variants (MSI and ASI) for myocardial work impairment in patients with STEMI and to assess their clinical applicability. By integrating hemodynamic parameters with multimodal imaging data, our work not only provides novel insights into the clinical utility of SI, MSI, and ASI but also establishes a scientific foundation for the rapid identification of myocardial dysfunction in emergency settings. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-965/rc).

Methods

Study design and population

The study protocol was approved by the Human Research Ethics Committee of Yangpu Hospital, School of Medicine, Tongji University (approval No. LL-2023-SCI-018). Written informed consent was obtained from all participants or their legally authorized representatives prior to enrollment. This investigation strictly adhered to the ethical principles outlined in the Declaration of Helsinki and its subsequent amendments. Consecutive patients presenting with first-time STEMI were included in this prospective observational study between March 2024 and January 2025. The eligibility criteria were as follows: age ≥18 years, ischemic symptoms persisting >30 minutes but <12 hours, ≥2 mm ST-segment elevation in ≥2 contiguous electrocardiographic leads, angiographically confirmed coronary occlusion, and successful primary PCI. Meanwhile, the exclusion criteria were previous myocardial infarction or revascularization, ventricular arrhythmias [sustained ventricular tachycardia (>30 seconds), frequent premature ventricular contractions (>10% of beats), or arrhythmias requiring urgent intervention (e.g., cardioversion/ablation) during index hospitalization], significant valvular pathology (aortic stenosis: mean gradient ≥40 mmHg or aortic valve area ≤1.0 cm²; mitral regurgitation: effective regurgitant orifice area ≥0.4 cm²; prosthetic valves or prior valvular surgery), hypertrophic cardiomyopathy [diagnosed by transthoracic echocardiography with maximal ventricular wall thickness ≥15 mm (or ≥13 mm with positive family history), unexplained by loading conditions], severe obesity [body mass index (BMI) ≥40 kg/m²], pulmonary emphysema [confirmed by thoracic computed tomography (CT) showing parenchymal destruction], and poor two-dimensional (2D) echo imaging quality [≥2 left ventricular segments with inadequate speckle tracking (frame-by-frame verification); endocardial border visibility <80% in any apical view (assessed by two sonographers)]. A sex-, age-, and cardiovascular risk factor-matched control group (n=37; diabetes, hypertension, and dyslipidemia) was recruited through institutional volunteers and community advertisements.

Blood pressure measurement

Brachial SBP and diastolic blood pressures (DBPs) were measured according to the 2024 American Heart Association Scientific Statement (16). After ≥5 minutes of supine rest, three consecutive readings were obtained at 1-minute intervals with an automated oscillometric device (Omron HEM-7322, Omron Healthcare, Kyoto, Japan) with a cuff size covering >80% of the upper arm circumference. Measurements were performed immediately before echocardiographic image acquisition, with the patient maintaining the same supine position. The average of the second and third readings was used for myocardial work analysis.

Anthropometry, hemodynamics, and biochemistry

BMI was calculated with the following formulas (17,18): BMI (kg/m²) = weight (kg)/height² (m²). MAP, SI, MSI, and ASI were calculated with the following formulae (19-22): MAP = DBP + 1/3 × (SBP − DBP); SI = heart rate [beats per minute (bpm)]/SBP (mmHg); MSI = heart rate (bpm)/MAP (mmHg); ASI = heart rate (beats per minute) × age (years)/SBP (mmHg). Laboratory examinations of blood creatine kinase (CK), creatine kinase myocardial band (CK-MB), high-sensitivity cardiac troponin I (hs-cTnI), and N-terminal prohormone of brain natriuretic peptide (NT-proBNP) before PCI were documented for all participants.

Comprehensive transthoracic echocardiography

All echocardiography studies were conducted by a board-certified radiologist (possessing three decades of expertise in echocardiography) using a Vivid E95 ultrasound system (GE HealthCare, Chicago, IL, USA) with an M5s phased-array transducer within 48 hours after PCI for patients and during initial evaluation for controls. All studies were analyzed offline with EchoPAC software v. 203 (GE HealthCare) by investigators blinded to clinical data. Left ventricular end-diastolic volume (LVEDV) and left ventricular end-systolic volume (LVESV) were measured by manual endocardial tracing via the biplane Simpson method, with papillary muscles included in the LV cavity. LVEF was calculated as follows: LVEF (%) = (LVEDV − LVESV)/LVEDV × 100%. Peak early diastolic mitral inflow velocity (E) and lateral mitral annular tissue velocity (e’) were acquired via pulsed-wave and tissue Doppler, respectively. Based upon the information provided, E/e’ ratio was calculated. Right ventricular systolic function was quantified through measurement of tricuspid annular plane systolic excursion (TAPSE) under M-mode echocardiography.

Speckle-tracking echocardiography

Apical two-, three-, and four-chamber views were acquired at 50–80 frames/second. Raw datasets were analyzed with dedicated speckle-tracking software (EchoPAC v. 203). Endocardial and epicardial borders were semiautomatically traced via automated function imaging (AFI), with manual adjustments as required. GLS was computed as the mean peak systolic strain across 17 myocardial segments. Myocardial work indices were derived offline with AFI-integrated pressure-strain loop analysis (EchoPAC v. 203), through a combination of GLS data with noninvasive LV pressure estimation. Peak systolic left ventricular pressure was assumed to be equivalent to brachial blood pressure. Key parameters included (23-25) (I) GWI (mmHg; total work within the area of the left ventricle pressure-strain loops calculated from mitral valve closure to mitral valve opening); (II) GCW (mmHg%; work performed by left ventricle segmental shortening during systole and lengthening during isovolumic relaxation, which contributes to left ventricle ejection); (III) GWW [mmHg%; work performed by left ventricle myocardial lengthening during systole and shortening during isovolumic relaxation, which does not contribute to LV ejection (represented as energy loss)]; and (IV) GWE [%; calculated from the ratio of constructive and wasted work as GCW/(GCW + GWW) × 100%]. A bull’s eye with GWI, GCW, GWW, and GWE values are displayed in Figure 1. For males, impaired myocardial work was defined as follows: GLS >−16%, GWI <1,270 mmHg%, GCW <1,650 mmHg%, GWW >238 mmHg%, and GWE <90%; meanwhile, for females, it was defined as follows: GLS >−16%, GWI <1,310 mmHg%, GCW <1,544 mmHg%, GWW >239 mmHg%, and GWE <91% (26). Gender-specific reference ranges for myocardial work indices are shown in Table 1.

Figure 1 Bull’s-eye plots showing left ventricular 17-segment longitudinal peak systolic strain, time to peak (A), the pressure-strain loops curve of myocardial work index (B), and the pressure-strain loops curve of myocardial work efficiency (C) in a patient with acute ST-segment elevation myocardial infarction. BP, blood pressure; GCW, global constructive work; GLS, global longitudinal strain; GWE, global work efficiency; GWI, global work index; GWW, global wasted work; HR, heart rate; LVP, left ventricular pressure; PSD, peak strain dispersion.

Statistical analysis

Continuous variables following a normal distribution are presented as the mean ± standard deviation and analyzed with the independent Student t-test. Nonnormally distributed variables are expressed as the median and interquartile range and were compared with the Mann-Whitney test. Categorical data are expressed as frequencies (percentages) and were assessed with the Fisher exact test. Bivariate correlations between SI and its variants and myocardial work indices were examined via Pearson correlation coefficients. To assess the discriminative capacity of SI and its variants for identifying impaired myocardial work, receiver operating characteristic (ROC) curve analysis was employed, with optimal cutoff values determined through maximum Youden index calculations. A post hoc power analysis was conducted with G*Power software (version 3.1.9.7) to determine the statistical power of our study. The analysis was based on the observed effect size (Cohen d =0.8) for the primary endpoint of GWI between groups, with an α error probability set at 0.05. Given our total sample size of 74 patients (37 per group), the achieved power was calculated to be 0.92, exceeding the conventional threshold of 0.80, thus indicating a sufficient sample size to detect the observed effect. All statistical tests adopted a two-sided significance threshold of P<0.05. Statistical computations were conducted with SPSS version 19.0 (IBM Corporation, Armonk, NY, USA) along with MedCalc software version 16.8.4 (MedCalc Software Ltd., Ostend, Belgium).

Results

Baseline characteristics

From March 2024 to January 2025, 42 patients with STEMI were initially enrolled. Five patients were excluded due to poor 2D echo imaging quality, resulting in 37 patients included in the final analysis. The most common infarct locations were the left ventricular anterior wall, inferior wall, apex, lateral wall, and anterior septum. A detailed summary of baseline characteristics is provided in Table 2. Compared to the controls, patients with STEMI showed no significant differences in age, gender, heart rate, blood pressure, comorbidities, or medications (P>0.05). However, SI and MSI were significantly higher in patients with STEMI, whereas ASI did not differ between the groups. Compared to controls, patients with STEMI had significantly elevated levels of hs-cTnI (P=0.007), CK (P<0.0001), CK-MB (P<0.0001), and NT-proBNP (P<0.0001). LVEDV and the E/e’ ratio was significantly greater in patients with STEMI, whereas LVEF and TAPSE were decreased (P<0.05). GWI, GCW, and GWE were significantly lower in patients with STEMI, whereas GLS and GWW were significantly higher (P<0.05) (Figure 2).

Figure 2 Comparison of cardiac function parameters LVEF (A), GLS (B), GWI (C), GCW (D), GWW (E), GWE (F) between controls and patients with ST-segment elevation myocardial infarction. GCW, global constructive work; GLS, global longitudinal strain; GWE, global work efficiency; GWI, global work index; GWW, global wasted work; LVEF, left ventricular ejection fraction; STEMI, ST-segment elevation myocardial infarction.

Correlation analysis

As shown in Table 3, SI, MSI, and ASI were negatively correlated with GWI and GCW (r=−0.79 to −0.64; all P values <0.0001) but positively correlated with GLS (r=0.51 to 0.63; P values <0.0001). SI and MSI demonstrated stronger correlations with GWI and GCW (coefficients of −0.75 and −0.79, respectively) than did ASI (coefficients of −0.64 and −0.65, respectively) (P<0.05). SI and MSI were also negatively correlated with GWW (P<0.05) but showed no significant correlation with GWE (P>0.05). ASI was negatively correlated with GWE (P<0.05) but not with GWW (P>0.05).

ROC analysis

The performance of SI, MSI and ASI in predicting impaired myocardial work is summarized in Table 4 and Figure 3. SI and MSI showed excellent predictive ability for GWI and GCW impairment (AUC =0.85–0.90). In contrast, ASI had moderate value for predicting impairment of all myocardial work indices and the weakest performance for GWW changes, with an AUC of approximately 0.6.

Figure 3 Receiver operating characteristic curve showing the performance of shock index, modified shock index, and age-adjusted shock index in identifying impaired myocardial work in patients with ST-segment elevation myocardial infarction. AUC, area under the receiver operating characteristic curve; GCW, global constructive work; GLS, global longitudinal strain; GWE, global work efficiency; GWI, global work index; GWW, global wasted work.

Discussion

Our data suggest that myocardial work indices serve as effective early markers of microvascular dysfunction in patients with STEMI. Although LVEF was significantly lower in patients with STEMI than in controls (52.66%±8.16% vs. 61.92%±3.77%; P<0.0001), the alterations in myocardial work indices were even more pronounced. GWI and GCW were significantly reduced, while GWW was markedly elevated (by more than 1.5-fold), reflecting pathophysiological energy dissipation likely due to microvascular obstruction-induced stiffness gradients. This positions myocardial work as a hemodynamic bridge between cellular pathology and systemic perfusion, mechanistically explaining SI’s prognostic power: impaired myocardial efficiency drives compensatory tachycardia and blood pressure dysregulation.

To our knowledge, this is the first study to investigate the capacity of SI, MSI, and ASI to predict myocardial work impairment in patients with STEMI. Our results demonstrated that SI and MSI outperformed ASI in predicting GWI and GCW impairment, with AUC values of >0.85. However, SI, MSI, and ASI all showed limited predictive capacity for GLS, GWW, and GWE, with AUC values of <0.80. This divergence in predictive performance arises from their differential ability to capture acute pathophysiological features.

SI and MSI capture the sympathetic storm responses following coronary occlusion. In this process, tachycardia and α-adrenergic-mediated vasoconstriction lead to characteristic hemodynamic changes, which may include an initial maintenance or even rise in SBP alongside a pronounced elevation in diastolic pressure.

MSI, by incorporating MAP (MAP = diastolic + 1/3 pulse pressure) better reflects diastolic coronary perfusion. In contrast, ASI (heart rate × age/SBP) overemphasizes chronic degenerative factors (e.g., β-receptor desensitization and arterial stiffness) (27-31) in older adults, which can mask acute signals. For instance, older adult patients (>75 years) with severe ischemia may show only mild tachycardia (e.g., 90 bpm) due to sinoatrial node dysfunction. In this context, ASI overestimates risk via age multiplication, whereas SI/MSI align with true acute load changes. GWI and GCW directly reflect left ventricular pressure-volume loop changes, which are closely tied to systolic afterload. MSI’s MAP integrates systolic ejection resistance and diastolic perfusion, whereas ASI’s reliance on SBP is distorted by “pseudonormalization” in stiffened arteries (e.g., falsely elevated SBP due to reduced aortic compliance). ASI’s linear age multiplier (heart rate × age/SBP) oversimplifies nonlinear cardiovascular aging, causing risk overestimation in individuals of geriatric age. For example, an 80-year-old’s ASI may be artificially inflated by the age multiplier, but actual myocardial injury may plateau due to chronic fibrosis, whereas SI and MSI more directly reflect acute load changes.

Notably, SI, MSI, and ASI all showed limited predictive capacity for myocardial deformation parameters (e.g., GLS) and energy metabolism parameters (e.g., GWW and GWE). This limitation stems from three mechanisms: first, GLS quantifies longitudinal myocardial deformation, with impairment beginning within a few seconds of coronary occlusion (ischemic stunning), a phase preceding significant sympathetic activation that alters heart rate or blood pressure, rendering SI, MSI and ASI unable to detect early mechanical deformation abnormalities (32-34). Second, GWW and GWE abnormalities are linked to subcellular events such as mitochondrial dysfunction and calcium mishandling (35-37), while SI, MSI, and ASI, as macroscale circulatory metrics, reflect only global oxygen balance and cannot capture microlevel metabolic disturbances. For example, reactive oxygen species bursts during reperfusion injury may reduce GWE by 30%, yet SI may pseudonormalize due to blood pressure recovery, decoupling their correlation. Finally, GLS and GWE are less influenced by left ventricular afterload, whereas SI calculation (HR/SBP) is highly afterload-dependent. Clinically, nitroglycerin-induced afterload reduction may elevate SI (suggesting higher risk) but improve GWE, creating paradoxical associations.

Our study identified optimal cutoff values of SI (0.40–0.70), MSI (0.80–0.95), and ASI (33.00–36.00) for predicting impaired myocardial work. The lower cutoff values for impaired myocardial work in our study, compared to those predicting mortality in sepsis, heart failure, burn, or shock (38-41), likely reflect certain key differences. Our patient population was probably at an earlier disease stage, where subtle, subclinical impairment is significant. In contrast, studies predicting mortality involve critically ill patients with severe, acute myocardial dysfunction, requiring higher cutoffs. Furthermore, the sensitive nature of myocardial work parameters allows them to detect minor hemodynamic changes that are prognostic in our specific context. Therefore, our lower cutoffs do not indicate an error but rather highlight the clinical value of identifying early myocardial dysfunction in our cohort. The clinical application of these cutoffs is straightforward: paramedics or triage nurses can calculate the SI or MSI immediately upon patient arrival. A result exceeding our proposed thresholds should signal high-risk STEMI, prompting expedited transfer to the catheterization laboratory, preparation for potential hemodynamic instability, and consideration of intensified monitoring and early invasive management—even in the absence of overt shock signs.

This study involved several limitations that should be addressed: (I) the relatively small sample size and single-center design might have introduced selection bias, as prehospital deaths or postresuscitation cases were excluded. This narrows the generalizability of our findings. Although the study was prospective, the sample size increases the susceptibility to type II errors. It is important to note that the substantial effect sizes observed (Cohen d =0.8) may be susceptible to overestimation despite a post hoc analysis indicating sufficient power. Consequently, our proposed cutoff values require further validation in larger, prospective, multicenter cohorts to confirm their robustness and clinical utility across diverse healthcare settings before widespread implementation can be recommended. (II) Myocardial work analysis depends on operator-dependent echocardiographic techniques, and inter-vendor software differences may affect reproducibility despite standardized protocols. (III) Dynamic effects of vasoactive agents (e.g., nitroglycerin and norepinephrine) on shock indices were not systematically analyzed. (IV) Finally, a lack of long-term follow-up restricted comprehensive prognostic validation. Future multicenter prospective studies with artificial intelligence-powered automated analysis are needed to confirm findings and refine risk models.

Conclusions

This study demonstrates that traditional SI and MSI outperform ASI in predicting myocardial work impairment (GWI/GCW) in STEMI. SI and MSI directly capture acute heart rate-blood pressure derangements, reflecting oxygen supply-demand mismatch and afterload changes, while ASI’s overcorrection for chronic age-related factors reduces acute injury sensitivity. Clinically, SI or MSI should be prioritized for early risk assessment, particularly in young patients with preserved vascular compliance. Future research should integrate hemodynamic and tissue-specific biomarkers to optimize myocardial salvage strategies.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-965/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-965/dss

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-965/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study protocol was approved by the Human Research Ethics Committee of Yangpu Hospital, School of Medicine, Tongji University (approval No. LL-2023-SCI-018). Written informed consent was obtained from all participants or their legally authorized representatives prior to enrollment. The investigation strictly adhered to the ethical principles outlined in the Declaration of Helsinki and its subsequent amendments.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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