Association Between TCBI (Triglycerides, Total Cholesterol, and Body Weight Index) and Stroke-Associated Pneumonia in Acute Ischemic Stroke Patients - PubMed (original) (raw)

Association Between TCBI (Triglycerides, Total Cholesterol, and Body Weight Index) and Stroke-Associated Pneumonia in Acute Ischemic Stroke Patients

Yufeng Liu et al. Clin Interv Aging. 2024.

Abstract

Purpose: Stroke-associated pneumonia (SAP) usually complicates stroke and is linked to adverse prognoses. Triglycerides, total cholesterol, and body weight index (TCBI) is a new and simple calculated nutrition index. This study seeks to investigate the association between TCBI and SAP incidence, along with its predictive value.

Patients and methods: Nine hundred and sixty-two patients with acute ischemic stroke were divided into SAP group and Non-SAP group. The TCBI was divided into three layers: T1, TCBI < 948.33; T2, TCBI 948.33-1647.15; T3, TCBI > 1647.15. Binary Logistic regression analysis was used to determine the relationship between TCBI levels and the incidence of SAP. Furthermore, restricted cubic splines (RCS) analysis was utilized to evaluate the influence of TCBI on the risk of SAP.

Results: TCBI in the SAP group was markedly lower compared to that in the Non-SAP group (P < 0.001). The Logistic regression model revealed that, using T3 layer as the reference, T1 layer had the highest risk for SAP prevalence (OR = 2.962, 95% CI: 1.600-5.485, P = 0.001), with confounding factors being controlled. The RCS model found that TCBI had a linear relationship with SAP (P for nonlinear = 0.490, P for overall = 0.004). Moreover, incorporating TCBI into the A2DS2 (Age, atrial fibrillation, dysphagia, sex, and severity) model substantially enhanced the initial model's predictive accuracy.

Conclusion: Low TCBI was associated with a higher risk of SAP. In clinical practice, TCBI has shown predictive value for SAP, contributing to early intervention and treatment of SAP.

Keywords: TCBI; acute ischemic stroke; nutritional status; stroke-associated pneumonia.

© 2024 Liu et al.

PubMed Disclaimer

Conflict of interest statement

The authors report no conflicts of interest in this work.

Figures

Figure 1

Figure 1

Patient flowchart.

Figure 2

Figure 2

Forest plot of odds ratios for SAP.

Figure 3

Figure 3

Association of TCBI with risk of stroke-associated pneumonia. Odds ratios and 95% confidence intervals derived from restricted cubic spline regression, with knots placed at the 5th, 35th, 65th, and 95th percentiles of the distribution of Log TCBI. The reference point is the median of Log TCBI. Odds ratios were adjusted for the same variables as model in. Figure 2.

Figure 4

Figure 4

Comparison of AUROC of TCBI with other biomarkers for predicting SAP.

References

    1. Kishore AK, Vail A, Chamorro A, et al. How is pneumonia diagnosed in clinical stroke research? A systematic review and meta-analysis. Stroke. 2015;46(5):1202–1209. doi: 10.1161/STROKEAHA.114.007843 - DOI - PubMed
    1. Badve MS, Zhou Z, van de Beek D, et al. Frequency of post-stroke pneumonia: systematic review and meta-analysis of observational studies. Int J Stroke. 2019;14(2):125–136. doi: 10.1177/1747493018806196 - DOI - PubMed
    1. de Montmollin E, Ruckly S, Schwebel C, et al. Pneumonia in acute ischemic stroke patients requiring invasive ventilation: impact on short and long-term outcomes. J Infect. 2019;79(3):220–227. doi: 10.1016/j.jinf.2019.06.012 - DOI - PubMed
    1. Li J, Zhang P, Wu S, et al. Stroke-related complications in large hemisphere infarction: incidence and influence on unfavorable outcome. Ther Adv Neurol Disord. 2019;12:1756286419873264. doi: 10.1177/1756286419873264 - DOI - PMC - PubMed
    1. Eltringham SA, Kilner K, Gee M, et al. Impact of dysphagia assessment and management on risk of stroke-associated pneumonia: a systematic review. Cerebrovasc Dis. 2018;46(3–4):99–107. doi: 10.1159/000492730 - DOI - PubMed

MeSH terms

Substances

LinkOut - more resources