Can prognostic nutritional index and systemic immune‐inflammatory index predict disease severity in COVID‐19?

Abstract

Background Prognostic nutritional index (PNI) and systemic immune‐inflammatory index (SII) are inflammation‐based novel markers that predict the prognosis in various patient populations. We have investigated the relationship between the disease severity in COVID‐19, and the PNI and SII scores in the present study. Materials and Methods This cross‐sectional retrospective study included 118 hospitalised patients with a confirmed diagnosis of COVID‐19. The patients were divided into two groups as those who were hospitalised at the intensive care unit (ICU) and those who had been internalised at the clinic (non‐ICU). Results Of the 118 patients, 50.8% were male. The mean age was 57.7 ± 17.5 years in non‐ICU patients and 70.3 ± 11.7 years in ICU patients and the difference was statistically significant ( P < .001). The lymphocyte count and the albumin levels were significantly lower in ICU patients ( P < .001, P < .001, respectively). The PNI score was significantly lower in ICU patients compared with non‐ICU patients ( P < .001). The SII score was found to be significantly higher in ICU patients compared with non‐ICU patients ( P < .001). The value of PNI and SII scores in prediction of the disease severity in COVID‐19 was evaluated with the ROC analysis (PNI: AUC = 0.796, 95%CI: 0.715‐0.877, P < .001; SII: AUC =0.689, 95% CI: 0.559‐0.819, P =.004). When the cut‐off value was taken as ≤36.7 for the PNI score, it was found to have 73.4% sensitivity and 70.8% specificity for predicting of the disease severity and ICU admission probability was 4.4 times higher. When the cut‐off value was taken as ≥813.6 for SII score, it was found to have 70.8% sensitivity and 66.0% specificity for predicting of the disease severity and ICU admission probability was six times higher. Conclusion The PNI and the SII scores are independent predictors of the prognosis and the disease severity in COVID‐19 patients who require hospitalisation at the ICU.

Predicting progression to severe COVID-19 using the PAINT score

“…There were many predict score models for disease severity in COVID-19 patients, including early warning score, National Early Warning Score 2, q-COVID score, prognostic nutritional index score, Brescia‑COVID Respiratory Severity Scale score, systemic immune-inflammatory index score, COVID-GRAM score, etc. [ 18 , 32 – 34 ] However, the important information of immune cells was not involved. To predict the risk of progression, we developed the new, predictive PAINT score which contained the NK cells.…”

“…Moreover, score prediction models, such as prognostic nutritional index (PNI), Systemic immune-inflammatory index (SII) have been used to predict prognosis in COVID-19 patients and other diseases [ 14 – 18 ]. However, the risk factors related to the progression of COVID-19 symptoms from mild/moderate to severe are still limited and need to be assessed.…”

Systemic immune‐inflammation index to predict placenta accreta spectrum and its histological subtypes

“…It has been linked to the severity of inflammatory diseases and infections in several studies 22,23 . It was recently used to predict the prognosis of COVID‐19 infection 24 . In the field of obstetrics, SII has only been used in a few studies.…”

“…22,23 It was recently used to predict the prognosis of COVID-19 infection. 24 In the field of obstetrics, SII has only been used in a few studies. Tanacan et al showed a relationship between high SII values and negative neonatal outcomes in pregnant women with preterm premature ruptures of membranes (PPROM).…”

Association of Prognostic Nutritional Index with Severity and Mortality of Hospitalized Patients with COVID-19: A Systematic Review and Meta-Analysis

“…The risk of the bias of study participation in two studies was considered unclear because of the inclusion of patients with severe COVID-19 [28] or those admitted to ICU [32]. The other studies demonstrated a low risk of bias in all domains [11,[19][20][21][29][30][31][33][34][35][36]. The overall risk of bias was considered to be low in the majority (84.6%) of studies.…”