DOI: 10.1161/circ.148.suppl_1.17240 ISSN: 0009-7322

Abstract 17240: Preoperative Pectoralis Muscle Area Index is Associated With Increased Post-LVAD Length of Stay and 90-day Readmission

Matthew R Carey, Annamaria Ladanyi, Mia Nishikawa, Abraham Bordon, Alberto Pinsino, Farhana Latif, Gabriel T Sayer, Koji Takeda, Nir Uriel, Paolo C Colombo, Melana Yuzefpolskaya
  • Physiology (medical)
  • Cardiology and Cardiovascular Medicine

Background: In LVAD pts, preoperative sarcopenia, as measured by pectoralis muscle area index (PMI), has been associated with mortality and GI bleed; however, the association with length of stay (LOS) and readmission is unknown.

Methods: This was a single-center retrospective cohort study of pts who underwent LVAD 01/2015-10/2018. Preoperative pectoralis muscle area was measured on CT chest prior to implant using Tera Recon, adjusted for height squared to give the PMI. Multivariable negative binomial regressions were used to assess the association between PMI and LOS. Subhazard ratios (SHR) and cause-specific hazard ratios (CSHR) were used to assess the association between PMI and freedom from 90-day readmission.

Results: Of 254 LVAD pts, 95 had a preop CT chest and were included (median days CT to LVAD: 7 [IQR 3-13]). Pts with PMI in the lowest quartile (PMI < 4.86 cm 2 /m 2 ) constituted the low PMI cohort; all others served as the reference cohort. Baseline characteristics are shown in the Table. During index hospitalization, 2 low PMI pts died vs 7 reference; 0 low PMI pts were transplanted vs 2 reference. Low PMI was associated with longer post-LVAD LOS (adjusted incidence rate ratio 1.31 [95% CI 1.03-1.66], p =0.03) and increased risk of 90-day readmission (aSHR, accounting for risk of death and transplantation, 3.77 [1.17-12.1], p =0.03; aCSHR 3.67 [1.35-9.96], p =0.01) (Fig). The most common reason for readmission in low PMI pts was infection (n=3).

Conclusions: Low PMI is associated with longer LOS and higher likelihood of 90-day readmission after LVAD. PMI could be used to identify sicker patients at risk for more intensive medical intervention and potentially higher health care cost.

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