The predictive value of systemic immune inflammation index on long-term outcomes among acute pulmonary embolism patients

Journal of Health Sciences and Medicine(2021)

Cited 0|Views1
No score
Abstract
Aim: Systemic immune-inflammation index (SII) is a novel marker that predicts adverse clinical outcomes among patients with malignancy and cardiovascular diseases. In the present study, we hypothesized that SII could provide more additional information in the prediction of long-term mortality among patients with acute pulmonary embolism (APE). Methods: Consecutive patients (n=514) who were followed up and treated with a diagnosis of APE were included in the study. The study group was divided into those survivors and non-survivors. Demographic, clinical, laboratory, and echocardiographic characteristics were compared between groups. Results: A total of 28 (5.4%) patients died in the 30 days. Besides, during a follow-up period of 29 [12-53] months, 52 patients (10.1%) died. In the Cox-regression analysis, age [odds ratio (OR): 1.052, 95% confidence interval (CI): 1.034–1.071; p < 0.01], right ventricle end-diastolic diameter basal (OR: 3.227, 95% CI: 1.902–5.474; p < 0.001), left ventricular ejection fraction (OR: 0.968, 95% CI: 0.948–0.988) and SII index (OR: 2.129, 95% CI: 1.290–3.515) were the independent predictors of overall mortality among the study population. In the receiver operator characteristic curve analysis, the area under the curve values of the SII index for overall mortality was 0.703 (95% CI: 0.629–0.777). SII with an optimal cutoff value of 1111 × 109 predicted the overall mortality with a sensitivity of 72% and specificity of 51%. Conclusion: The SII index, an inexpensive and easily calculable parameter, was a strong predictor of overall mortality in patients with APE.
More
Translated text
Key words
acute pulmonary embolism patients,acute pulmonary embolism,systemic immune inflammation index,long-term
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined