Predictive Value of Prognostic Nutritional Index on COVID-19 Severity

A Diagnostic Nomogram for Predicting Hypercapnic Respiratory Failure in Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease

Purpose

To develop and validate a nomogram for assessing the risk of developing hypercapnic respiratory failure (HRF) in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD).

Patients and Methods

From January 2019 to August 2023, a total of 334 AECOPD patients were enrolled in this research. We employed the Least Absolute Shrinkage and Selection Operator (LASSO) regression and multivariate logistic regression to determine independent predictors and develop a nomogram. This nomogram was appraised by the area under the receiver operating characteristic curve (AUC), calibration curve, Hosmer-Lemeshow goodness-of-fit test (HL test), decision curve analysis (DCA), and clinical impact curve (CIC). The enhanced bootstrap method was used for internal validation.

Results

Sex, prognostic nutritional index (PNI), hematocrit (HCT), and activities of daily living (ADL) were independent predictors of HRF in AECOPD patients. The developed nomogram based on the above predictors showed good performance. The AUCs for the training, internal, and external validation cohorts were 0.841, 0.884, and 0.852, respectively. The calibration curves and HL test showed excellent concordance. The DCA and CIC showed excellent clinical usefulness. Finally, a dynamic nomogram was developed (https://a18895635453.shinyapps.io/dynnomapp/).

Conclusion

This nomogram based on sex, PNI, HCT, and ADL demonstrated high accuracy and clinical value in predicting HRF. It is a less expensive and more accessible approach to assess the risk of developing HRF in AECOPD patients, which is more suitable for primary hospitals, especially in developing countries with high COPD-related morbidity and mortality.

Prognostic nutritional index as a predictive marker for acute kidney injury in adult critical illness population: a systematic review and diagnostic test accuracy meta-analysis

BACKGROUND

The prognostic nutritional index (PNI), integrating nutrition and inflammation markers, has been increasingly recognized as a prognostic predictor in diverse patient cohorts. Recently, its effectiveness as a predictive marker for acute kidney injury (AKI) in various clinical settings has gained attention. This study aims to assess the predictive accuracy of the PNI for AKI in critically ill populations through systematic review and meta-analysis.

METHODS

A systematic review was conducted using the databases MEDLINE, EMBASE, PubMed, and China National Knowledge Infrastructure up to August 2023. The included trials reported the PNI assessment in adult population with critical illness and its predictive capacity for AKI. Data on study characteristics, subgroup covariates, and diagnostic performance of PNI, including sensitivity, specificity, and event rates, were extracted. A diagnostic test accuracy meta-analysis was performed. Subgroup analyses and meta-regression were utilized to investigate the sources of heterogeneity. The GRADE framework evaluated the confidence in the meta-analysis's evidence.

RESULTS

The analysis encompassed 16 studies with 17 separate cohorts, totaling 21,239 patients. The pooled sensitivity and specificity of PNI for AKI prediction were 0.67 (95% CI 0.58-0.74) and 0.74 (95% CI 0.67-0.80), respectively. The pooled positive likelihood ratio was 2.49 (95% CI 1.99-3.11; low certainty), and the negative likelihood ratio was 0.46 (95% CI 0.37-0.56; low certainty). The pooled diagnostic odds ratio was 5.54 (95% CI 3.80-8.07), with an area under curve of summary receiver operating characteristics of 0.76. Subgroup analysis showed that PNI's sensitivity was higher in medical populations than in surgical populations (0.72 vs. 0.55; p < 0.05) and in studies excluding patients with chronic kidney disease (CKD) than in those including them (0.75 vs. 0.56; p < 0.01). Overall, diagnostic performance was superior in the non-chronic kidney disease group.

CONCLUSION

Our study demonstrated that PNI has practical accuracy for predicting the development of AKI in critically ill populations, with superior diagnostic performance observed in medical and non-CKD populations. However, the diagnostic efficacy of the PNI has significant heterogeneity with different cutoff value, indicating the need for further research.

Predictive Value of Nutrition and Inflammation-Related Indices on Prognosis in Type 2 Diabetes Mellitus Patients with Coronavirus Disease-2019

Objectives

This study aimed to demonstrate how the prognostic nutritional index (PNI) and systemic immune-inflammatory index (SII) help predict the severity and prognosis of patients with type 2 diabetes (T2DM) and coronavirus disease (COVID-19).

Methods

This retrospective cohort study included 501 T2DM patients (male, 42.1%; female, 57.9%) who were hospitalized due to COVID-19 between April 2020 and December 2020. The patients were divided into survivors and non-survivors. After comparing demographic and laboratory data between the groups, the correlation of PNI and SII with clinical and laboratory data was evaluated.

Results

The median (interquartile) ages of the non-survivor and survivor groups were 74 (15) and 69 (14) years, respectively, and the difference was significant (p<0.001). The PNI was significantly lower in the non-survivor group than in the survivor group (p<0.001). The SII was significantly higher in the non-survivor group than in the survivor group (p<0.001). PNI was negatively correlated with glucose levels (r=-0.115, p=0.011). If the cut-off PNI value of 29.1 was used, it had a sensitivity and specificity of 76.2% and 76.3%, respectively, in predicting the severity of the illness and the risk of death in T2DM patients.

Conclusion

Consequently, the PNI and SII levels are effective in predicting survival and disease severity in patients with COVID-19 and T2DM.

Preoperative prognostic nutritional index predicts postoperative delirium in aged patients after surgery: A matched cohort study

OBJECTIVE

Prognostic nutritional index (PNI) is an indicator to evaluate the nutritional immune status of patients. This study aimed to assess whether preoperative PNI could predict the occurrence of postoperative POD in aged patients undergoing non-neurosurgery and non-cardiac surgery.

METHOD

The aged patients undergoing non-neurosurgery and non-cardiac surgery between January 2014 and August 2019 were included in the retrospective cohort study. The correlation between POD and PNI was investigated by univariate and multivariable logistic regression analysis, propensity score matching (PSM), inverse probability of treatment weighting (IPTW), and subgroup analysis.

RESULTS

In the cohort (n = 29,814), the cutoff value of PNI was 46.01 determined by the receiver operating characteristic (ROC) curve. In univariate and three multivariable regression analysis, the ORs of PNI ≤ 46.01 was 2.573(95% CI:2.261-2.929, P < 0.001),1.802 (95% CI:1.567-2.071, P < 0.001),1.463(95% CI:1.246-1.718, P < 0.001),1.370(95% CI:1.165-1.611, P < 0.001). In the PSM model and IPTW model, the ORs of PNI ≤ 46.01 were 1.424(95% CI:1.172-1.734, P < 0.001) and 1.356(95% CI:1.223-1.505, P < 0.001).

CONCLUSION

The PNI was found to have a predictive value for POD in patients undergoing non-neurosurgery and non-cardiac surgery. Improving preoperative nutritional status may be beneficial in preventing POD for aged patients.

The need for biomarkers to determine response to enteral nutrition during and after critical illness: an update

PURPOSE OF REVIEW

Biomarkers proposed to provide prognosis or to determine the response to enteral nutrition have been assessed in a number of experimental and clinical studies which are summarized in the current review.

RECENT FINDINGS

There are several pathophysiological mechanisms identified which could provide biomarkers to determine response to enteral nutrition. Several biomarkers have been studied, most of them insufficiently and none of them has made its way to clinical practice. Available studies have mainly assessed a simple association of a biomarker with outcomes, but are less focused on dynamic changes in the biomarker levels. Importantly, studies on pathophysiology and clinical features of gastrointestinal dysfunction, including enteral feeding intolerance, are also needed to explore the mechanisms potentially providing specific biomarkers. Not only an association of the biomarker with any adverse outcome, but also a rationale for repeated assessment to assist in treatment decisions during the course of illness is warranted.

SUMMARY

There is no biomarker currently available to reliably provide prognosis or determine the response to enteral nutrition in clinical practice, but identification of such a biomarker would be valuable to assist in clinical decision-making.

Evaluation of Inflammation-Based Prognostic Risk Scores in Predicting in-Hospital Mortality Risk in COVID-19 Patients: A Cross-Sectional Retrospective Study

Objective

Systemic inflammatory parameters are predictors of poor prognosis in COVID-19 patients. This study evaluated whether the prognostic nutritional index, which was also related to nutrition risk and other inflammation-based prognostic scores, was predictive of in-hospital mortality in COVID-19 patients.

Materials and Methods

This was a retrospective cross-sectional single-center study. Based on the exclusion criteria, 151 patients over 18 years old diagnosed with COVID-19 and hospitalized in the intensive care unit between March 2020 and December 2020 were eligible for this study. Multivariable logistic regression analysis was performed to evaluate the predictive value of the Glasgow Prognostic Score (GPS), Prognostic Index (PI), Prognostic Nutritional Index (PNI), and Systemic Inflammatory Index (SII).

Results

In the univariate analyses, age, diabetes mellitus (DM), chronic kidney disease, acute kidney injury, hypothyroidism, hospitalization stay, lactate dehydrogenase (LDH), aspartate aminotransferase (AST), D-dimer, ferritin, C-reactive protein (CRP), albumin, hemoglobin level, platelet count, urea, creatinine level, PNI, GPS were significantly associated with mortality. However, in the multivariable logistic regression analysis of the inflammation-based prognostic scores, only PNI was statistically significant in predicting in-hospital mortality (OR=0.83; [95% CI=0.71-0.97]; p =0.019).

Conclusion

PNI is a more useful and powerful tool among these inflammation-based prognostic risk scores in predicting in-hospital mortality in COVID-19 patients.

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

The associations of prognostic nutritional index (PNI) with disease severity and mortality in patients with coronavirus disease 2019 (COVID-19) remain unclear. Electronic databases, including MEDLINE, EMBASE, Google scholar, and Cochrane Library, were searched from inception to 10 May 2022. The associations of PNI with risk of mortality (primary outcome) and disease severity (secondary outcome) were investigated. Merged results from meta-analysis of 13 retrospective studies (4204 patients) published between 2020 and 2022 revealed a lower PNI among patients in the mortality group [mean difference (MD): −8.65, p < 0.001] or severity group (MD: −5.19, p < 0.001) compared to those in the non-mortality or non-severity groups. A per-point increase in PNI was associated with a reduced risk of mortality [odds ratio (OR) = 0.84, 95% CI: 0.79 to 0.9, p < 0.001, I2 = 67.3%, seven studies] and disease severity (OR = 0.84, 95% CI: 0.77 to 0.92, p < 0.001, I2 = 83%, five studies). The pooled diagnostic analysis of mortality yielded a sensitivity of 0.76, specificity of 0.71, and area under curve (AUC) of 0.79. Regarding the prediction of disease severity, the sensitivity, specificity, and AUC were 0.8, 0.61, and 0.65, respectively. In conclusion, this study demonstrated a negative association between PNI and prognosis of COVID-19. Further large-scale trials are warranted to support our findings.

Nutritional Risk Assessment Scores Effectively Predict Mortality in Critically Ill Patients with Severe COVID-19

Background: Malnutrition predicts a worse outcome for critically ill patients. However, quick, easy-to-use nutritional risk assessment tools have not been adequately validated. Aims and Methods: The study aimed to evaluate the role of four biological nutritional risk assessment instruments (the Prognostic Nutritional Index—PNI, the Controlling Nutritional Status Score—CONUT, the Nutrition Risk in Critically Ill—NUTRIC, and the modified NUTRIC—mNUTRIC), along with CT-derived fat tissue and muscle mass measurements in predicting in-hospital mortality in a consecutive series of 90 patients hospitalized in the intensive care unit for COVID-19-associated ARDS. Results: In-hospital mortality was 46.7% (n = 42/90). Non-survivors had a significantly higher nutritional risk, as expressed by all four scores. All scores were independent predictors of mortality on the multivariate regression models. PNI had the best discriminative capabilities for mortality, with an area under the curve (AUC) of 0.77 for a cut-off value of 28.05. All scores had an AUC above 0.72. The volume of fat tissue and muscle mass were not associated with increased mortality risk. Conclusions: PNI, CONUT, NUTRIC, and mNUTRIC are valuable nutritional risk assessment tools that can accurately predict mortality in critically ill patients with COVID-19-associated ARDS.

Prognostic Nutritional Index and Oxygen Therapy Requirement Associated With Longer Hospital Length of Stay in Patients With Moderate to Severe COVID-19: Multicenter Prospective Cohort Analyses

Purpose

To evaluate whether the prognostic nutritional index (PNI) is related to the oxygen therapy requirement at hospital admission and to ascertain the prognostic effect of the PNI and the oxygen therapy requirement as predictors of hospital length of stay in patients with moderate to severe coronavirus disease 2019 (COVID-19).

Methods

This is a post-hoc analysis in hospitalized patients with moderate to severe COVID-19. The participants were categorized: (1) non-oxygen therapy (moderate COVID-19 not requiring oxygen therapy); (2) nasal cannula therapy (severe COVID-19 requiring nasal cannula oxygen therapy); and (3) high-flow therapy (severe COVID-19 requiring high-flow oxygen therapy). PNI was calculated for each patient according to the following equation: serum albumin [g/dL] × 10 + total lymphocyte count [per mm³] × 0.005. The participants were categorized into malnutrition (PNI <40), mild malnutrition (PNI 40-45), and non-malnutrition (PNI > 45).

Results

According to PNI, malnutrition was more prevalent in the high-flow therapy group (94.9%; P < 0.001) with significantly lower PNI compared to both groups even after adjusting for the center and C-reactive protein. Patients in the high-flow therapy group [9 days (95% CI 7.2, 10.7), P < 0.001] and malnutrition status [7 days (95% CI 6.6, 7.4), P = 0.016] showed a significant longer hospital length of stay compared to their counterparts. The multivariable Cox proportional hazard models showed significant associations between both oxygen therapy requirement and PNI categories and hospital discharge.

Conclusion

In addition to oxygen therapy requirement, low PNI was associated with longer hospital length of stay. Our findings suggest that PNI could be useful in the assessment of nutritional status related to the prognosis of patients with moderate to severe COVID-19.

Clinical Value of Prognostic Nutritional Index in Prediction of the Presence and Severity of Neonatal Sepsis

Purpose

The prognostic nutritional index (PNI) is a common indicator of nutritional and inflammatory status and is associated with various diseases such as cancer, cardiovascular diseases and infectious diseases. However, to date, no study has concentrated on the role of PNI in assessing and predicting the presence and severity of neonatal sepsis. Therefore, the present study aimed to explore the association of the PNI with the presence and severity of neonatal sepsis.

Materials and Methods

A total of 1196 neonates with suspected sepsis were enrolled in this study and their complete clinical and laboratory data were collected. PNI was calculated as serum albumin (g/L) + 5 × total lymphocyte count (10⁹/L). Multivariate logistic regression analysis was performed to identify the risk factors for the presence and severity of neonatal sepsis. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the predictive value of PNI. All statistical analyses were performed using the statistical package SPSS 24.0.

Results

PNI was lower in neonates with sepsis and decreased significantly with the severity of sepsis. The correlation analysis demonstrated that the PNI was negatively correlated with the levels of the inflammatory marker procalcitonin (PCT) and C-reactive protein (CRP), and the length of hospital stay. Multivariate logistic regression analysis revealed that the PNI was independently and inversely associated with the presence and severity of neonatal sepsis. The area under the ROC curve of the PNI was 0.64 (95% confidence interval (CI): 0.61–0.67, P < 0.001) for severe sepsis and 0.69 (95% CI: 0.60–0.78, P < 0.001) for septic shock. In addition, our data revealed that PNI was also independently correlated with the length of hospital stay.

Conclusion

PNI is an independent predictor for the presence and severity of neonatal sepsis.

Omega-3 index is directly associated with a healthy red blood cell distribution width

Low red blood cell (RBC) membrane content of EPA and DHA, i.e., the omega-3 index (O3I), and elevated RBC distribution width (RDW) are risk factors for all-cause mortality. O3I and RDW are related with membrane fluidity and deformability. Our objective was to determine if there is a relationship between O3I and RDW in healthy adults. Subjects without inflammation or anemia, and with values for O3I, RDW, high-sensitivity C-reactive protein (CRP), body mass index (BMI), age and sex were identified (n = 25,485) from a clinical laboratory dataset of  > 45,000 individuals. RDW was inversely associated with O3I in both sexes before and after (both p < 0.00001) adjusting models for sex, age, BMI and CRP. Stratification by sex revealed a sex-O3I interaction with the RDW-O3I slope (p < 0.00066) being especially steep in females with O3I ≤ 5.6%. In healthy adults of both sexes, the data suggested that an O3I of > 5.6% may help maintain normal RBC structural and functional integrity.

Early Prediction of Disease Progression in Patients with Severe COVID-19 Using C-Reactive Protein to Albumin Ratio

Background

Early identification of patients with severe coronavirus disease (COVID-19) at an increased risk of progression may promote more individualized treatment schemes and optimize the use of medical resources. This study is aimed at investigating the utility of the C-reactive protein to albumin (CRP/Alb) ratio for early risk stratification of patients.

Methods

We retrospectively reviewed 557 patients with COVID-19 with confirmed outcomes (discharged or deceased) admitted to the West Court of Union Hospital, Wuhan, China, between January 29, 2020 and April 8, 2020. Patients with severe COVID-19 (n = 465) were divided into stable (n = 409) and progressive (n = 56) groups according to whether they progressed to critical illness or death during hospitalization. To predict disease progression, the CRP/Alb ratio was evaluated on admission.

Results

The levels of new biomarkers, including neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, CRP/Alb ratio, and systemic immune-inflammation index, were higher in patients with progressive disease than in those with stable disease. Correlation analysis showed that the CRP/Alb ratio had the strongest positive correlation with the sequential organ failure assessment score and length of hospital stay in survivors. Multivariate logistic regression analysis showed that percutaneous oxygen saturation (SpO2), D-dimer levels, and the CRP/Alb ratio were risk factors for disease progression. To predict clinical progression, the areas under the receiver operating characteristic curves of Alb, CRP, CRP/Alb ratio, SpO2, and D-dimer were 0.769, 0.838, 0.866, 0.107, and 0.748, respectively. Moreover, patients with a high CRP/Alb ratio (≥1.843) had a markedly higher rate of clinical deterioration (log − rank p < 0.001). A higher CRP/Alb ratio (≥1.843) was also closely associated with higher rates of hospital mortality, ICU admission, invasive mechanical ventilation, and a longer hospital stay.

Conclusion

The CRP/Alb ratio can predict the risk of progression to critical disease or death early, providing a promising prognostic biomarker for risk stratification and clinical management of patients with severe COVID-19.

Efficacy of Ninjin'yoeito in treating severe coronavirus disease 2019 in patients in an intensive care unit

Coronavirus Disease-2019 (COVID-19), an infectious disease associated with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), is a global emergency with high mortality. There are few effective treatments, and many severe patients are treated in an intensive care unit (ICU). The purpose of this study was to evaluate whether the Japanese Kampo medicine ninjin'yoeito (NYT) is effective in treating ICU patients with COVID-19. Nine patients with confirmed SARS-CoV-2 infection admitted to the ICU were enrolled in this study. All patients underwent respiratory management with invasive mechanical ventilation (IMV) and enteral nutrition. Four patients received NYT (7.5 g daily) from an elemental diet tube. We retrospectively examined the prognostic nutritional index (PNI), length of IMV, length of ICU stay, length of hospital stay, rate of tracheostomy, and mortality rate. The median age of the enrolled participants was 60.0 years (4 men and 5 women). The median body mass index was 27.6. The most common comorbidity was diabetes (4 patients, 44%), followed by hypertension (3 patients, 33%) and chronic kidney disease (2 patients, 22%). The median length of IMV, ICU stay, and hospital stay were all shorter in the NYT group than in the non-NYT group (IMV; 4.0 days vs 14.3 days, ICU; 5.3 days vs 14.5 days, hospital stay; 19.9 days vs 28.2 days). In the NYT and non-NYT groups, the median PNI at admission was 29.0 and 31.2, respectively. One week after admission, the PNI was 30.7 in the NYT group and 24.4 in non-NYT group. PNI was significantly (p = 0.032) increased in the NYT group (+13.6%) than in the non-NYT group (-22.0%). The Japanese Kampo medicine NYT might be useful for treating patients with severe COVID-19 in ICU. This study was conducted in a small number of cases, and further large clinical trials are necessary.

Can prognostic nutritional index predict mortality in intensive care patients with COVID-19?

OBJECTIVES

PNI is a calculated parameter using the albumin and the lymphocyte count from the CBC, which demonstrates the immunological and nutritional status of the patient. The aim of this study is to show the relationship between PNI and mortality in COVID-19 patients and to reveal a PNI cut-off value for mortality.

MATERIALS AND METHODS

Data of 690 PCR positive COVID-19 ICU patients were recorded. COVID-19 ICU patients were divided into two groups; the first group consisted of survivors, while the second group consisted of patients who died in the ICU. Patients were also evaluated in two groups according to the PNI cut-off value that predicted mortality (PNI ≤ 42.00, PNI ≥ 43) and were compared in terms of demographics, laboratory parameters, clinical findings and mortality rates.

RESULTS

When 690 COVID-19 patients were divided into two groups as survivors (50.6%) and deceased (49.4%) in intensive care, PNI value was significantly lower in the deceased group compared to the surviving group (P < .001). The PNI cut-off value predicting mortality was determined as ≤42. Patients were classified into two groups according to the PNI cut-off value. PNI ≤42 was determined as an independent risk factor for mortality (OR:2.9 P < .001). AUC values for PNI, albumin, and lymphocyte were 0.628, 0.612, and 0.590, respectively; P < .001 for all.

CONCLUSION

PNI is an inexpensive method that can be easily calculated on the basis of routine laboratory parameters. We believe that the PNI value of COVID-19 patients on admission to the ICU may be an independent factor to predict mortality.

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

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.

Clinical significance of prognostic nutrition index in hospitalized patients with COVID-19: Results from single-center experience with systematic review and meta-analysis

BACKGROUND

We aimed to ascertain risk indicators of in-hospital mortality and severity as well as to provide a comprehensive systematic review and meta-analysis to investigate the prognostic significance of the prognostic nutrition index (PNI) as a predictor of adverse outcomes in hospitalized coronavirus disease 2019 (COVID-19) patients.

METHODS

In this cross-sectional study, we studied patients with COVID-19 who were referred to our hospital from February 16 to November 1, 2020. Patients with either a real-time reverse-transcriptase polymerase chain reaction test that was positive for COVID-19 or high clinical suspicion based on the World Health Organization (WHO) interim guidance were enrolled. A parallel systematic review/meta-analysis (in PubMed, Embase, and Web of Science) was performed.

RESULTS

A total of 504 hospitalized COVID-19 patients were included in this study, among which 101 (20.04%) patients died during hospitalization, and 372 (73.81%) patients were categorized as severe cases. At a multivariable level, lower PNI, higher lactate dehydrogenase (LDH), and higher D-dimer levels were independent risk indicators of in-hospital mortality. Additionally, patients with a history of diabetes, lower PNI, and higher LDH levels had a higher tendency to develop severe disease. The meta-analysis indicated the PNI as an independent predictor of in-hospital mortality (odds ratio [OR] = 0.80; P < .001) and disease severity (OR = 0.78; P = .009).

CONCLUSION

Our results emphasized the predictive value of the PNI in the prognosis of patients with COVID-19, necessitating the implementation of a risk stratification index based on PNI values in hospitalized patients with COVID-19.

Comparison of systemic immune-inflammation index (SII), early warning score (ANDC) and prognostic nutritional index (PNI) in hospitalized patients with malignancy, and their influence on mortality from COVID-19

Introduction

We evaluated several biological indicators based on inflammation and/or nutritional status, such as systemic immune-inflammation index (SII), early warning score (ANDC) and prognostic nutritional index (PNI) in hospitalized COVID-19 patients with and without malignancies for a prognostic significance.

Methodology

This is a retrospective and observational study on 186 patients with SARS-CoV-2, who were diagnosed with COVID-19 by real-time PCR testing and hospitalized due to COVID-19 pneumonia. 75 patients had various malignancies, and the rest (111), having a similar age and comorbidity profile based on propensity score matching, had no malignancy.

Results

None of the measures as neutrophil to lymphocyte ratio, platelet to lymphocyte ratio, monocyte to lymphocyte ratio, SII, PNI or ANDC was found to be significantly different between two groups. Odds ratio for the mortality, OR 2.39 (%95 CI 1.80–3.16) was found to be significantly higher for the malignancy group, even though the duration of hospitalization was statistically similar for both groups. PNI was found to be significantly lower for deceased patients compared with survivors in the malignancy group. Contrarily, ANDC was found to be significantly higher for deceased patients in the malignancy group.

Conclusions

PNI and ANDC have independent predictive power on determining the in-hospital death in COVID-19 malignancy cases. It is suggested that ANDC seems to be a more sensitive score than SII in COVID-19 cases with malignancies.