Aims <p>This investigation aims to estimate the diagnostic value of global longitudinal strain (GLS) and myocardial work (MW) indices for the identification of subclinical left ventricular (LV) systolic impairment (SLVSI) in individuals with simple obesity, obesity and prediabetes, and obesity and type 2 diabetes mellitus (T2DM).</p> Methods <p>This investigation included 302 participants: 225 obese patients and 77 healthy individuals. LV GLS and MW-derived values, namely, the global constructive work (GCW), global work index (GWI), global wasted work (GWW), and global work efficiency (GWE), were analyzed. All individuals with obesity were classified into three groups: simple obesity, individuals with obesity and prediabetes, and individuals with obesity and T2DM. Comparisons of the LV GLS and MW were conducted among the four groups. The independent factors that affected the SLVSI in individuals with obesity were assessed using a logistic regression model. We conducted an ROC analysis to estimate the performance of MW in detecting SLVSI in individuals with obesity.</p> Results <p>Significant differences were detected in the GWI, GCW, LV GLS, GWW, and GWE among normal controls, individuals with simple obesity, individuals with obesity and prediabetes, and individuals with obesity and T2DM (<i>P</i> &lt; 0.05). The combination of the GCW, GWW, GWI, and GWE resulted in the best AUC (0.896) for the determination of SLVSI in individuals with obesity. After adjustment for confounders, prediabetes or T2DM was independently associated with an absolute LV GLS &lt; 20% in obese individuals.</p> Conclusions <p>It is feasible to use LV GLS and MW-related parameters to determine SLVSI in individuals with obesity, individuals with obesity and prediabetes, and individuals with obesity and T2DM. Even in the preclinical stage prior to the onset of diabetes, prediabetes still has an incremental effect on SLVSI in obese patients.</p>

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Prediabetes and diabetes exacerbated cardiac systolic function in obese patients at the subclinical stage: insights from global longitudinal strain and myocardial work

  • Kai Lu,
  • Guang-an Li,
  • Yan-jiao Wang,
  • Jun Huang

摘要

Aims

This investigation aims to estimate the diagnostic value of global longitudinal strain (GLS) and myocardial work (MW) indices for the identification of subclinical left ventricular (LV) systolic impairment (SLVSI) in individuals with simple obesity, obesity and prediabetes, and obesity and type 2 diabetes mellitus (T2DM).

Methods

This investigation included 302 participants: 225 obese patients and 77 healthy individuals. LV GLS and MW-derived values, namely, the global constructive work (GCW), global work index (GWI), global wasted work (GWW), and global work efficiency (GWE), were analyzed. All individuals with obesity were classified into three groups: simple obesity, individuals with obesity and prediabetes, and individuals with obesity and T2DM. Comparisons of the LV GLS and MW were conducted among the four groups. The independent factors that affected the SLVSI in individuals with obesity were assessed using a logistic regression model. We conducted an ROC analysis to estimate the performance of MW in detecting SLVSI in individuals with obesity.

Results

Significant differences were detected in the GWI, GCW, LV GLS, GWW, and GWE among normal controls, individuals with simple obesity, individuals with obesity and prediabetes, and individuals with obesity and T2DM (P < 0.05). The combination of the GCW, GWW, GWI, and GWE resulted in the best AUC (0.896) for the determination of SLVSI in individuals with obesity. After adjustment for confounders, prediabetes or T2DM was independently associated with an absolute LV GLS < 20% in obese individuals.

Conclusions

It is feasible to use LV GLS and MW-related parameters to determine SLVSI in individuals with obesity, individuals with obesity and prediabetes, and individuals with obesity and T2DM. Even in the preclinical stage prior to the onset of diabetes, prediabetes still has an incremental effect on SLVSI in obese patients.